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Performance Management

James W. Smither

La Salle University

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Latham and his colleagues (Latham & Mann, 2006; Latham, Almost, Mann, & Moore,

2005) recently noted that there has been a paradigm shift from thinking of performance appraisal

as a discrete event to a continuous process of performance management where coaching is

inherent in the process. This paradigm shift follows the recognition that performance appraisal

research became too interested in measurement issues and not interested enough in examining

how performance can be enhanced (DeNisi & Pritchard, 2006). Because of this paradigm shift,

Latham and Mann state that their review “may be the last review of the literature where

performance appraisal is in the title” (p. 296). This chapter is the first to appear in a handbook of

industrial and organizational psychology where the focus is on performance management rather

than performance appraisal.

Several definitions of performance management have been offered and most share

common elements. Aguinis (2009; Aguinis & Pierce, 2008) defines performance management as

“a continuous process of identifying, measuring, and developing the performance of individuals

and teams and aligning performance with the strategic goals of the organization.” Cascio (2006)

states that performance management involves defining performance (e.g., setting goals and

assessing progress toward goals), facilitating performance (e.g., providing adequate resources,

staffing effectively, removing roadblocks to successful performance), and encouraging

performance (providing timely and fair rewards for successful performance). den Hartog,

Boselie, and Paauwe (2004) state that performance management involves defining, measuring,

and stimulating employee performance with the goal of improving the organization‟s

performance. Hedge and Borman (2008) state that performance management is more than an

annual performance review meeting between a supervisor and employee and that performance

management includes ongoing coaching, feedback, and support from the supervisor. Finally,

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Heslin, Carson, and VandeWalle (2009) state simply, “Performance management involves all the

initiatives whereby managers strive to guide and motivate high performance by employees.” In

sum, the key elements of performance, at a minimum, include goal setting, feedback, employee

development (and coaching), performance evaluation, and rewarding performance.

Aguinis (2009) argues that effective performance management systems offer many

potential advantages. These include greater clarity about organizational goals as well as the

behaviors and results required for successful employee performance, enhancing employees‟

understanding of their strengths and weaknesses (and hence valuable developmental activities),

increasing employees‟ motivation, competence, and self-esteem, better distinguishing between

good and poor performers and thereby increasing the fairness of administrative decisions (such

as pay increases, promotions, and terminations), protecting the organization from lawsuits, and

facilitating organizational change. At the same time, Aguinis (2009) notes that ineffective

performance management systems have the potential to waste time and money, damage

relationships, decrease motivation and job satisfaction, increase employee turnover, create

perceptions of unfairness and thereby increase risks of litigation.

This chapter begins by defining job performance. Research concerning each of the core

elements of performance management is then reviewed: goal setting, feedback, developing

employees (including coaching), evaluating performance, and rewarding performance. Next,

several topics are reviewed that are of special interest to performance management: contextual

performance, counterproductive work behavior, team performance, the role of technology, cross-

cultural issues, and perceptions of fairness. Finally, directions for future research are presented.

Defining Job Performance

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There is no universally accepted definition of „job performance.‟ Most authors argue that

job performance is best defined by employee behaviors. For example, Campbell, McCloy,

Oppler, and Sager (1993, pp. 40–41) stated that performance is

“something that people actually do and can be observed. By definition, it includes only

those actions or behaviors that are relevant to the organization‟s goals and that can be

scaled (measured) in terms of each person‟s proficiency (e.g., level of contribution).

Performance is what the organization hires one to do, and do well. Performance is not

the consequence or result of action, it is the action itself. Performance consists of goal-

relevant actions that are under the control of the individual, regardless of whether they

are cognitive, motor, psychomotor, or interpersonal.”

Other authors have also emphasized that job performance should be conceptualized as

behaviors under the control of the employee that are related to organizational goals (Murphy &

Cleveland, 1991; Rotundo & Sackett, 2002).

In contrast, Bernardin, Hagan, Kane, and Villanova (1998) define performance as the

record of outcomes produced on a specified job function, activity, or behavior during a specified

time period. Their definition makes clear that performance is something separate and distinct

from the person who produced it or that person's characteristics (e.g., traits). They do however

include in their definition of a „performance outcome‟ how frequently a performer exhibits a

behavior related to some aspect of value such as quantity, quality, timeliness, cost effectiveness,

interpersonal impact, and need for supervision. For example, the record of outcomes for the

behavior „seeks input from knowledgeable parties before making a decision‟ would be the

frequency of this behavior relative to all possible occasions when the employee had an

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opportunity to seek such input before making a decision. Finally, they argue that the definitions

of outcomes should be derived from important critical internal and external customers.

Motowidlo (2003, p. 39) defined job performance as “the total expected value to the

organization of the discrete behavioral episodes that an individual carries out over a standard

period of time.” He also draws a distinction between behavior (what people do), performance

(expected organizational value of what people do), and results (states or conditions that are

changed by what people do in ways that contribute to or detract from organizational

effectiveness).

Both broad and more differentiated models of job performance can play a useful role in

understanding and predicting job performance (Bartram, 2005). Borman & Motowidlo (1993)

introduced the important distinction between task performance and contextual performance (or

organizational citizenship behaviors, Podsakoff, Ahearne & MacKenzie, 1997). Contextual

performance (organizational citizenship behavior) includes personal support (e.g., helping and

cooperating with coworkers), organizational support (e.g., following organizational policies,

presenting a favorable view of the organization to others), and conscientious initiative (e.g.,

showing initiative and displaying extra effort to complete work) (Borman, Buck, Hanson,

Motowidlo, Stark, & Drasgow, 2001). The distinction between task performance and contextual

performance is supported by research showing that ability is a better predictor of task

performance than is personality, whereas personality is a better predictor of contextual

performance than is ability (Borman, Penner, Allen, & Motowidlo, 2001).

Several models of performance further disaggregate the criterion domain. For example,

Campbell et al. (1993) presented an eight-factor model of work performance: job-specific task

proficiency, non-job-specific task proficiency, written and oral communication, demonstrating

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effort, maintaining personal discipline, facilitating team and peer performance, supervision and

leadership, and management and administration. Bartram (2005), defining competencies as sets

of behaviors that are instrumental in the delivery of desired results or outcomes, proposed eight

broad performance competencies: leading and deciding, supporting and cooperating, interacting

and presenting, analyzing and interpreting, creating and conceptualizing, organizing and

executing, adapting and coping, and enterprising and performing. Analyzing multi-source

feedback ratings, Scullen, Mount, and Judge (2003) created a performance model with four

factors: technical skills, administrative skills, human skills, and citizenship behaviors.

The importance of including counterproductive behaviors (e.g., antisocial behavior,

incivility, sabotaging equipment, stealing from the company, blaming or gossiping about

coworkers, deviant behaviors, withholding effort) in a taxonomy of work behaviors has also been

noted by several authors (Motowidlo, 2003; Robinson & Bennett, 1995; Rotundo & Sackett,

2002; Sackett, 2002).

Recently, the importance of adaptive performance (i.e., adapting to complex, novel,

turbulent, or unpredictable work environments), both for teams and individuals, has been

recognized as an important aspect of job performance (Chen, Thomas, & Wallace, 2005; Ford,

Smith, Weissbein, Gully, & Salas, 1998; Kozlowski, Gully, Brown, Salas, Smith, & Nason,

2001; Marks, Zaccaro, & Mathieu, 2000). Pulakos, Arad, Donovan, and Plamondon (2000)

developed a taxonomy of adaptive performance that includes eight dimensions: handling

emergencies or crisis situations, handling work stress, solving problems creatively, dealing with

uncertain and unpredictable work situations, learning work tasks, technologies, and procedures,

demonstrating interpersonal adaptability, demonstrating cultural adaptability, and demonstrating

physically oriented adaptability.

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Other authors have drawn attention to the importance acknowledging that performance

changes over time (Reb & Cropanzano, 2007; Schmitt, Cortina, Ingerick, & Wiechmann, 2003)

and that, in addition to mean performance over time, performance trends (e.g., flat, linear-

improving, linear-deteriorating, U-shaped, ∩-shaped) influence performance ratings. Ployhart

and Hakel (1998) found that there were individual differences in intraindividual performance

variability over time and that these differences could be predicted moderately well by biodata.

In the applied context of performance management, both employee behaviors and the

outcomes or results of those behaviors are important. Also, performance management is

concerned with task performance, contextual performance, counterproductive work behavior,

adaptive performance, and changes in performance over time.

The Role of Goals in Performance Management

A central premise of performance management systems is that individual (and team)

goals need to be closely aligned with higher-level organizational goals. For example, Schiemann

(2009) describes how Continental Airlines selected on-time performance to be an organization-

wide goal in part because so many different roles (e.g., logistics, pilots, flight attendants, gate

agents, maintenance, baggage handlers) can affect on-time performance. On-time performance

thereby served as a unifying goal for different functional groups across the organization.

At the individual level, goal setting is also an important element of effective performance

management (Latham & Mann, 2006; Heslin, Carson, & VandeWalle, 2009). Perhaps the most

central tenant of goal setting theory, illustrated in hundreds of studies, is that specific, difficult

goals lead to higher performance than „do your best‟ goals (Locke & Latham, 1990). Moreover,

specific, difficult goals have positive effects not only for individuals and teams but also for

organizations (Baum, Locke, & Smith, 2001; Rogers & Hunter, 1991). Research indicates that

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the benefits of goals occur because goals focus employees‟ attention on a specific objective

(rather than other activities), lead to higher levels of effort to attain those objectives, enhance

persistence in the face of setbacks and obstacles, and stimulate employees to develop new

approaches and strategies when faced with complex tasks (Latham, 2004; Locke & Latham,

2002, Heslin, Carson, & VandeWalle, 2009).

Self-efficacy (i.e., the employee‟s belief that he or she can attain the goal) also plays a

central role in goal setting research. Social cognitive theory (Bandura, 1986) argues that self-

efficacy, goal setting, anticipated outcomes, and reinforcements work together to help people

attain their goals. Self-efficacy influences choices about what behaviors to undertake, the

amount of effort to put forth, and how much one should persist when faced with obstacles. High

self-efficacy leads to higher levels of effort and persistence, which in turn lead to higher

performance, which in turn enhances self-efficacy. Self-efficacy can be enhanced by providing

the employee with mastery experiences (e.g., by breaking down complex tasks into smaller,

easier steps that gradually become more challenging), enabling the employee to observe a role-

model (who is perceived as similar to the employee on a number of attributes) successfully

perform the task, and providing verbal encouragement that the employee has the ability to learn

and perform the task successfully (Heslin, Carson, & VandeWalle, 2009).

A meta-analysis by Klein and colleagues (Klein, Wesson, Hollenbeck, & Alge, 1999)

found that goal commitment is important if goals are to affect performance and this is especially

true when goals are difficult. Goal commitment can be strengthened in several ways (Locke &

Latham, 2002; Heslin, Carson, & VandeWalle, 2009) including having people make a public

commitment to the goal (Cialdini, 2001), increasing self-efficacy, and increasing the

attractiveness of outcomes associated with goal attainment (e.g., by communicating a compelling

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vision, providing monetary incentives, or changing employees‟ perceptions concerning the

consequences of attaining or not attaining the goal, Latham, 2001).

One concern is that setbacks or failures experienced during the pursuit of goals might

lower self-efficacy. This is less likely to occur when people have an implicit belief that ability is

malleable (and can therefore be developed over time with persistent effort) rather than fixed

(Wood & Bandura, 1989). The implicit belief that ability is fixed has been labeled an entity

theory of ability whereas the implicit belief that ability is malleable has been labeled an

incremental theory of ability (Dweck, 1986; and more recently referred to as a growth mindset,

Dweck, 2006). Research indicates that the belief that ability is malleable can be enhanced by

telling people their skills can be developed via practice (Wood & Bandura, 1989) and by praising

effort (rather than ability) following successful performance (Mueller & Dweck, 1998).

Meta-analysis (Wood, Mento, & Locke, 1987) shows that the benefits of difficult goals

on performance are diminished when task complexity is high (e.g., when the task involves many

acts and information cues that are interrelated and change over time; referred to by Wood, 1986,

as component complexity, coordinative complexity, and dynamic complexity). Moreover,

assigning challenging distal goals during the early stages of skill acquisition on a complex task

can lead to decrements in performance (Kanfer & Ackerman, 1989). However, proximal (i.e.,

short-term, intermediate) goals can be helpful (when coupled with distal goals) during the early

stages of skills acquisition on complex tasks (Latham & Seijts, 1999). Feedback related to

proximal goals can provide (a) markers of progress (thereby increasing self-efficacy) and (b)

information that can help people change strategies when it appears that their current task

strategies are suboptimal (Latham & Seijts, 1999). Providing learning goals during the early

stages of skills acquisition on complex tasks can also be helpful because such goals direct

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attention to learning the task rather than worrying about a distal performance outcome (Noel &

Latham, 2006; Winters & Latham, 1996).

The stress that can accompany a difficult goal can be perceived as either a challenge (e.g.,

the situation provides an opportunity for self-growth and coping strategies are available to deal

with the demands of the situation) or a threat (e.g., where failure seems likely and coping

strategies are not available). Drach-Zahavy and Erez (2002) showed that, when the situation was

perceived as a threat, a difficult goal on a complex task lowered performance; when the situation

was perceived as a challenge, the same difficult goal on the same complex task increased

performance. This is consistent with the finding that persistence and performance are higher

when goals are framed positively (e.g., emphasizing the consequences of attaining the goal)

rather than negatively (e.g., emphasizing the consequences of not attaining the goal; Roney,

Higgins, & Shah, 1995).

Goal setting also plays an important role in team performance (O‟Leary-Kelly,

Martocchio, & Frink, 1994). Heslin, Carson, and VandeWalle (2009) note that it is important for

individual goals to be aligned with team goals (and for team goals to be aligned with

organizational goals). A meta-analysis by Gully, Incalcaterra, Joshi, and Beaubien (2002) found

that team efficacy (the team‟s perceptions about whether it is capable of successfully performing

a specific task) was more strongly related to team performance when task, goal, and outcome

interdependence were high. That is, when the team context encourages cooperation among

members, team efficacy is more strongly related to performance than when it does not. Team

efficacy also affects the difficulty of team-set goals (Durham, Knight, & Locke, 1997).

Participation in setting team goals also yields more consistently positive effects than assigned

team goals (O‟Leary-Kelly et al., 1994).

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A recent meta-analysis (Payne, Youngcourt, & Beaubien, 2007) examined antecedents,

proximal consequences, and distal consequences of three dimensions of goal orientation (GO):

learning (approaching the task with the goal of learning for its own sake), prove performance

(the desire to prove, and gain favorable judgments about, one‟s competence), and avoid

performance (the desire to avoid disproving, and avoid negative judgments about, one‟s

competence). In terms of antecedents, although unrelated to cognitive ability, learning GO had a

small positive relationship with having an incremental view of intelligence (believing that

intelligence is malleable rather than fixed). It was positively associated with need for

achievement, conscientiousness, extraversion, openness to experience, agreeableness, emotional

stability, self-esteem, and general self-efficacy. The proximal consequences of learning GO

included higher levels of task-specific self-efficacy, self-set goals, effective learning strategies,

and feedback seeking, along with lower levels of state anxiety. The distal consequences of

learning GO included higher levels of learning, academic performance, and job performance.

Using a meta-correlation matrix, the authors found that learning GO predicted job performance

above and beyond cognitive ability and personality. In contrast, avoid performance GO

generally had negative relationships with the antecedents and consequences listed above while

prove performance GO was generally unrelated to the antecedents and consequences.

A meta-analysis by Rodgers and Hunter (1991) found that the widely used performance

management approach called management by objectives (MBO), which combines goal setting,

participation in decision making, and objective feedback, was associated with productivity gains

in 68 out of 70 studies. Also, when top-management‟s commitment to MBO was high, the

average gain in productivity was 56% versus only 6% when commitment from top-management

was low.

Organizational Goal Setting

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One trend related to organizational goal setting is the use of balanced scorecards. Kaplan

and Norton‟s (1992, 1996) balanced scorecard framework is based on the premise that focusing

only on financial goals and measures is insufficient because such measures are lag indicators

(i.e., they describe merely the outcomes of leaders‟ past actions) and can promote behavior that

sacrifices long-term value for short-term performance. Balanced scorecards select a limited

number of critical measures within each of four perspectives (financial, customer, internal

processes, learning and innovation). Recently, the balanced scorecard concept has been

extended to include strategy maps (Kaplan & Norton, 2004), which show the cause-and-effect

relationships among the multiple measures on a balanced scorecard, including leads, lags, and

feedback loops. Because balanced scorecards measure performance drivers as well as outcomes,

they provide indicators of future performance as well as an assessment of historical results.

Balanced scorecards are also based on the premise that firms with different strategies require

different measures. The mere use of financial and non-financial goals and measures does not

constitute a balanced scorecard. Instead, effective balanced scorecards are closely linked to the

organization‟s strategy so that people can understand the strategy by looking only at the

scorecard and its strategy map (Kaplan & Norton, 2001, 2004). Across all four perspectives there

are usually only 15 to 20 measures. Balanced scorecards can heighten awareness of the potential

tradeoffs among various goals and thereby help ensure that the organization does not optimize

one goal (e.g., profit) at the expense of another (e.g., customer satisfaction; Schiemann, 2009).

Examples of financial measures include economic value added, return on capital

employed, operating profit, cash flow, return on assets, project profitability, sales backlog, return

on equity, and earnings per share. Examples of customer measures include customer retention,

customer satisfaction (e.g., from surveys), on-time delivery, share of key accounts‟ purchases,

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market share, brand image, and the firm‟s share in the most profitable segments. Examples of

measures of internal business processes include quality, speed to market, rework, safety indices,

complaint resolution time, cycle time, yield, and unit cost. Examples of learning and innovation

measures include employee skill development, rate of improvement in key operational measures,

number and quality of employee suggestions, development time for the next generation of

products, percent of sales from new products, employee turnover, and employee satisfaction

(from surveys). In an experiment with MBA students, Ritchie-Dunham (2003) found that,

contrasted with a financial scorecard, a balanced scorecard positively affected decision makers'

mental models of how elements of a simulated firm dynamically interrelate, which led to

improved performance.

In sum, balanced scorecards can provide an overarching framework that drives and aligns

organizational, department, team, and individual goal setting. For example, in some

organizations, each employee and each team explicitly link their goals to specific elements in the

organization‟s balanced scorecard.

The Role of Feedback in Performance Management

Feedback plays a vital role in performance management in that, without feedback, the

effect of goals on performance is diminished (Erez, 1977; Locke & Latham, 1990; Neubert,

1998). Alvero, Bucklin, and Austin (2001) note that performance feedback has been defined in

several ways (e.g., information given to people about the quantity or quality of their past

performance, information about performance that allows the person to adjust his or her

performance) and that feedback can serve several functions (as an antecedent, reinforcer, or

punisher). Moreover, feedback can serve both an informational purpose and a motivational

purpose (Ilgen, Fisher, & Taylor, 1979). For example, information contained in feedback can

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help recipients learn and develop more effective task strategies. At the same time, the evaluative

nature of feedback can have an incentive (or disincentive) effect.

In their review of performance feedback in organizational settings, Alvero et al. (2001)

found that feedback yielded desired and consistent effects in 58% of the 64 applications they

reviewed, mixed effects (i.e., desired effects in some, but not all, of the participants, settings,

and/or behaviors analyzed) in 41% of the applications, and no effects in only 1% of the

applications. In a widely cited meta-analysis, Kluger and DeNisi (1996) found that feedback

interventions, on average, improved performance (d = .41), however, in about one-third of the

studies examined, feedback had a negative effect on performance. There was also large

variability among effect sizes and this variability could not be explained by feedback sign (i.e.,

positive vs. negative feedback), thereby suggesting that positive feedback leads to performance

improvement for some people (or in some situations), whereas negative feedback leads to

performance improvement for other people (or in other situations). Feedback can point to a gap

between one‟s goals and current performance without necessarily leading to efforts to improve

performance because, as Kluger and DeNisi (1996) noted, a goal-feedback gap can be reduced

by (a) increasing effort, (b) abandoning the goal, (c) changing (or lowering) the goal, or (d)

rejecting the feedback message.

Reactions and Responses to Feedback

Despite its importance, it is often noted that employees are sometimes reluctant to receive

and act on feedback (Cleveland, Lim, & Murphy, 2007). Receiving feedback that one is

„satisfactory‟ can be disappointing and can lead to a stable drop in organizational commitment

(Pearce & Porter, 1986). Moreover, feedback is often associated with affective reactions that, in

turn, can affect work performance (Kluger, Lewinsohn, & Aiello, 1996). Discouraging feedback

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and feedback that threatens the recipient‟s self-esteem decreases the effectiveness of feedback

interventions (Kluger & DeNisi, 1996). Comer (2007) found that receiving negative feedback

directly from the task itself was more intrinsically motivating and led to less negative emotion

than receiving negative feedback from interpersonal sources.

Kinicki, Prussia, Wu, and McKee-Ryan (2004) found that a set of cognitive variables

completely mediated the relationship between an employee‟s receipt of and response to

feedback. Specifically, a feedback-rich environment and perceiving the supervisor as credible

(e.g., trustworthy and competent) led to perceptions that the feedback was accurate, which in turn

affected the desire and intent to respond to the feedback, which in turn affected performance one-

year later.

Swann and Schroeder (1995) proposed that responses to feedback can proceed in three

phases, with each consecutive phase requiring more cognitive resources. During the first phase,

when people receive feedback they initially classify it as favorable or unfavorable and there is a

tendency to embrace positive feedback (i.e., consistent with a positivity or self-enhancement

striving). If sufficient motivation and cognitive resources are available, people proceed to the

second phase where they compare the feedback to their beliefs about who they actually are (i.e.,

the actual self) and react favorably to feedback that is consistent with their self-views (consistent

with a self-verification striving). If their self-view is uncertain, they will compare the feedback

to various possible selves (e.g., ideal self or ought self). If sufficient motivation and cognitive

resources remain available, people proceed to the third phase where they analyze the feedback

more carefully (a cost-benefit analysis). For example, at this phase people might consider

whether and how the feedback might be used to improve their performance. This depth of

processing model suggests that feedback recipients need to be encouraged to reflect on and

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analyze feedback (and be provided with the time and resources to do so) thereby creating the

possibility that they might use the feedback for self-improvement.

Self-evaluations (Atwater, 1998; Fletcher, 1986) can shape reactions to feedback. For

example, Korsgaard (1996) found that individuals who appraised themselves favorably were

more likely to agree with positive (rather than negative) feedback from others. For individuals

who appraised themselves unfavorably, agreement was unrelated to the favorableness of

feedback. At the same time, receiving favorable feedback had a larger, positive effect on the

subsequent performance of individuals who had appraised themselves unfavorably.

Feedback reactions can also be shaped by the recipient‟s personality and attitudes. For

example, Lam, Yik, and Schaubroeck (2002) examined responses to performance appraisal

feedback. They found that, for employees with low negative affectivity but not for employees

with high negative affectivity, attitudes of higher rated performers improved one month after

receiving a favorable appraisal and that these improved attitudes persisted six months after the

performance appraisal. The attitudes of lower rated employees did not change over time. Renn

(2003) proposed that high goal commitment (relative to low goal commitment) leads to more

effective acquisition, processing, and use of feedback, which in turn leads to higher performance.

In a study with rehabilitation counselors, he found that the amount of task feedback had a

positive relationship with work performance for counselors with high goal commitment but had a

negative relationship with performance for those counselors with low goal commitment.

Regulatory Focus and Reactions to Feedback

Higgins (1997, Brockner & Higgins, 2001) has distinguished between a promotion

regulatory focus that orients the person toward attaining positive outcomes versus a prevention

regulatory focus that orients the person toward minimizing negative outcomes. Promotion focus

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concerns striving for ideals (presumably set by the self) whereas prevention focus concerns being

motivated by oughts (often expectations established by others). Higgins has argued that

regulatory focus, in part, develops as a consequence of nurturance-oriented parenting (which

instills a promotion focus in children) or security-oriented parenting (which instills a prevention

focus). In this sense, regulatory focus can be thought of as a dispositional variable. However,

Higgins and others also acknowledge that regulatory focus can be situationally-induced (e.g.,

Thorsteinson & Highhouse, 2003; Van-Dijk & Kluger, 2004) and that the effects of regulatory

focus are comparable regardless of whether it varies as a function of persons (i.e., a dispositional

variable) or situations (Higgins, 1997). Indeed, research has shown that situational features can

make one or the other regulatory focus more accessible (at least temporarily) and thereby

influence the goals that people set and their persistence and achievement (Roney, Higgins, &

Shah, 1995).

It appears that self-regulatory focus can influence a person‟s emotional reactions and

subsequent responses to positive versus negative feedback. That is, a promotion-oriented

regulatory focus (i.e., on gains) might lead one to respond more positively to positive feedback

than would a prevention-oriented regulatory focus (i.e., on losses). Higgins, Shah, and Friedman

(1997) experimentally manipulated regulatory focus and found that a promotion focus (relative

to a prevention focus) led to a stronger increase in cheerfulness after success feedback, whereas a

prevention focus (relative to a promotion focus) led to a stronger increase in agitation after

failure feedback. Similar results were obtained by Idson, Liberman, and Higgins (2000). Van-

Dijk and Kluger (2004) suggested that task motivation (and hence effort and performance) will

increase when a person‟s self-regulatory focus is congruent with the sign of feedback. Idson and

Higgins (2000) found that chronic self-regulatory focus and feedback sign interacted to predict

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task performance such that people with a promotion focus improved their performance more

after positive feedback and people with a prevention focus improved their performance more

after negative feedback.

Delivering Feedback

Larson (1986) found that supervisors give feedback less often about poor performance

than good performance, although when given, feedback about poor performance was more

specific than feedback about good performance. When the supervisor‟s rewards were dependent

on employee performance, supervisors provided feedback more often when the employee

showed a pattern of gradually worsening performance.

Kluger and DeNisi (1996) state that feedback interventions affect performance by

changing the recipient‟s locus of attention and hence the allocation of cognitive resources. They

found that feedback that directs the recipient‟s attention to the task is more effective that

feedback that directs the recipient‟s attention to the self and away from the task (e.g., supervisor-

delivered or verbal feedback versus computer-delivered feedback, feedback designed to

discourage the recipient or that threatens the recipient‟s self-esteem). The review by Alvero et

al. (2001) found that feedback was more consistently effective when delivered via graphs with

written or verbal feedback than when delivered via verbal feedback, written feedback, or graphs

alone. Also, feedback was more consistently effective when delivered at the group level than

when delivered at the individual level.

Viswesvaran (2001) summarized the conditions for appraisal feedback to have a positive

effect as including a balanced review (both positive and negative) of the employee‟s

performance, discussing no more than two limitations in one meeting, a participative style that

allows the employee to state his or her views, and good ongoing communication between the

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supervisor and employee outside of the appraisal meeting. Ilgen and Davis (2000) have argued

that the most important issue when providing negative feedback is to strike a balance so that it

becomes possible for the recipient to accept responsibility for performance that did not meet

expectations while at the same time not lowering the recipient‟s self-concept. Finally, the Alvero

et al. (2001) review found that the feedback was more consistently effective when it was used in

combination with other procedures (e.g., antecedents such as training, job aids, or supervisory

prompts; goal setting; and/or behavioral consequences such as praise, monetary incentives, or

time off work for desired behavior).

Several cautions about delivering feedback are noteworthy. For example, one tenet of

performance management is the importance of providing ongoing, informal feedback to

employees. But providing (versus not providing) informal feedback affects subsequent ratings of

the employee. Larson and Skolnik (1985) found that giving informal feedback about good (or

poor) interpersonal performance subsequently led to more positive (or negative) ratings of

interpersonal performance (relative to ratings obtained when informal feedback had not been

provided), although this effect was not observed for task performance. Also, providing more

specific feedback (i.e., feedback that guides recipients to correct responses by helping them

identify behaviors that are appropriate or inappropriate for successful performance) is not always

beneficial. More specific feedback appears beneficial for performance during practice but can

discourage exploration during practice so that its advantages do not endure over time or transfer

to performance when the task is more complex and very specific feedback is no longer available

(Goodman & Wood, 2004; Goodman, Wood, & Hendrickx, 2004). Finally, by directing

attention to the self rather than the task, praise can detract from rather than enhance performance

on a cognitively demanding task (Kluger & DeNisi, 1996).

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Feedback Seeking

Employees are not merely passive recipients of feedback; they also actively seek

feedback (Ashford, Blatt, & VandeWalle, 2003; Ashford & Cummings, 1983) by using inquiry

(directly asking for feedback from others) or monitoring (observing the environment for

indications of how one is viewed by others and how one is performing). Employees can seek

feedback to satisfy one or more of three motives. One motive is instrumental (i.e., feedback can

help employees regulate their behavior and attain their goals). For example, as the perceived

diagnostic value of feedback increases, employees seek it more frequently, especially in

uncertain situations (e.g., when the employee is new to a job or when role ambiguity is high).

The instrumental value of feedback is also affected by the employee‟s goal orientation (learning

orientation is associated with more feedback seeking) and the source of feedback (feedback is

sought more often from one‟s supervisor and credible sources). Managers might be especially

likely to seek feedback because feedback is often less available to them (e.g., employees are less

likely to offer negative feedback to managers at high levels in the organization) and the nature of

their work is often more ambiguous than the work of others. A second motive for feedback

seeking is ego-based (i.e., to protect or enhance one‟s ego) and this can lead employees to avoid,

distort, or discount feedback, especially if they have a performance goal orientation. Consistent

with this motive, individuals with high self-confidence are more likely (and employees with low

performance expectations are less likely) to seek feedback. The third motive is image-based

(i.e., to protect or enhance the impressions that others hold about the employee). For example,

an employee might seek feedback from the supervisor shortly after an instance of good

performance (even if the feedback has no instrumental value) to make the performance salient to

the supervisor and elicit the supervisor‟s praise. In contrast, when employees think that seeking

21

feedback will make them look bad, they are less likely to use inquiry as a method of seeking

feedback (even if the feedback has instrumental value). Lam, Huang, and Snape (2007) found

that employee feedback seeking was positively related to the quality of the leader-member

exchange and to an objective measure of work performance, but only when supervisors

interpreted the employee‟s feedback seeking as reflecting the employee‟s desire to enhance

performance rather being driven by impression management motives.

Moss, Valenzi, and Taggart (2003) noted that the feedback management strategies of

poor performers have received relatively little research attention. Rather than seeking feedback,

poor performers might engage in feedback avoiding behavior (e.g., by avoiding interactions with

the supervisor). They might also engage in feedback mitigating behavior (e.g., by offering

excuses, apologizing, or telling the supervisor about the problem before the supervisor becomes

angry) to reduce the harshness of feedback they expect to receive. Moss et al. (2003) developed

a 17-item scale to measure feedback seeking, feedback mitigating, and feedback avoiding

behaviors.

The feedback environment can also affect the frequency and nature of feedback seeking.

For example, feedback seeking is more likely in a supportive environment (Williams, Miller,

Steelman, & Levy, 1999). Whitaker, Dahling, and Levy (2007), using the feedback environment

scale (Steelman, Levy, & Snell, 2004) found that employees who perceived a supportive

feedback environment (one where workplace characteristics encourage the use of active inquiry)

had increased feedback seeking, higher role clarity, and higher ratings of performance. Of

course, whether feedback seeking is viewed as a sign of insecurity is likely to be affected by the

organization‟s culture (which can therefore make feedback seeking more or less likely, London

& Smither, 2002).

22

The outcomes of feedback seeking are noteworthy. For example Renn and Fedor (2001)

found that feedback-seeking behavior increased goal setting which in turn improved

performance. Evidence has also indicated that seeking more negative feedback is associated

with higher effectiveness ratings from coworkers (Ashford & Tsui, 1991, Edwards, 1995).

Ashford and Northcraft (1992) found that feedback seeking generally enhanced rather than

diminished one‟s image, except for poor performers. Moreover, Ashford et al. (2003) note that

poor performers are disadvantaged because they both receive and seek less feedback.

Feedback in Team Settings

In many team settings, members have both individual and team goals. They need to

direct effort to attaining individual goals and responsibilities but also need to coordinate and

work cooperatively with other team members. In such settings, one practical issue is whether

feedback should focus on individual performance, team performance, or both. DeShon,

Kozlowski, Schmidt, Milner, and Wiechmann (2004) found that feedback (about individual

performance, team performance, or both) affected the way team members allocated their

resources such that team members who received feedback focused only on individual

performance focused their attention and effort on individual performance (and hence had the

highest level of individual performance), whereas team members who received feedback focused

only on team performance focused their attention and effort on team performance (and hence had

the highest team performance). It is noteworthy that team members who received both

individual and team-level feedback were not able to make optimal use of the feedback (i.e., the

highest levels of individual and team performance occurred when team members received

feedback focused on only individual or team performance, respectively).

The Productivity Measurement and Enhancement System

23

Pritchard, Harrell, DiazGranados, and Guzman (2008) recently meta-analyzed 83 field

studies of the Productivity Measurement and Enhancement System (ProMES), an intervention

aimed at enhancing the productivity of work units within organizations through performance

measurement and feedback. The implementation of ProMES begins with forming a design team

that establishes objectives, quantitative indicators of output, and contingencies (a graphic utility

function that relates the amount of each indicator to its value for the organization). The system is

then implemented by collecting data on the indicators and distributing a printed feedback to each

unit employee after each performance period. A feedback meeting is also held after each

performance period to review the feedback report and identify ways of making improvements.

The Pritchard et al. (2008) meta-analysis found that ProMES results in large improvements in

productivity in many different types of settings (e.g., type of organization, type of work and

worker, country) and that these effects are sustained over time (in some cases years). However,

ProMES was somewhat less effective in highly interdependent units, perhaps because feedback

focused on outputs (such as provided in ProMES) rather than processes is less effective for

highly interdependent units.

Multisource Feedback

Multisource feedback refers to collecting performance evaluations from more than one

source. A variant of multisource feedback, called 360-degree feedback, collects feedback from

key constituents who represent the full circle of relevant viewpoints: supervisor(s), peers, direct

reports, and in some cases customers. Self-ratings are sometimes also collected. The intent is to

help feedback recipients understand how they are viewed by others (and where necessary help

the recipient develop more realistic self-views, e.g., Atwater, Roush, & Fischthal, 1995)) and for

the recipient to use the feedback to set developmental goals and guide behavior change. A

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policy-capturing study by Greguras, Ford, and Brutus (2003) found that multisource feedback

recipients attended to all rater sources (peers, direct reports, and supervisors), but for certain

dimensions they attended to some rater sources more than others.

A review of research on multisource feedback (Smither, London, & Reilly, 2005) found

evidence for the concurrent validity of multisource ratings in that they are positively related to

assessment center performance, annual appraisals, objective performance data, and the

satisfaction and retention of subordinates. Also, raters in different roles (e.g., supervisors, peers,

direct reports) appear to share a common conceptualization of managerial performance

dimensions. Smither et al. (2005) then conducted a meta-analysis of 24 longitudinal studies and

found that improvement in direct report (d = .15), peer (d = .05), and supervisor ratings (d = .15)

over time is generally small. Moderator analyses found that improvement was greater when

feedback was used only for developmental purposes (rather than for administrative purposes).

Specifically, across rater sources (excluding self-ratings), the average effect size in the

developmental purpose studies was .25 (versus .08 in the administrative purpose studies). They

also found that a large percentage of variance in effect sizes was not explained by sampling

error, even after accounting for the effects of moderator variables, thereby indicating that other

factors likely affect the extent of behavior change associated with multisource feedback. They

presented a theoretical framework and reviewed empirical evidence suggesting performance

improvement is more likely for some feedback recipients than others. Specifically, improvement

is most likely to occur when feedback indicates that change is necessary, recipients have a

positive feedback orientation, perceive a need to change their behavior, react positively to the

feedback, believe change is feasible, set appropriate goals to regulate their behavior, and take

actions that lead to skill and performance improvement.

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In a study examining reactions to and behavior change after receiving multisource

feedback, Atwater and Brett (2005) found that leaders who expressed more motivation and had

more positive emotions immediately after receiving multisource feedback subsequently

improved in terms of direct reports‟ ratings (one year later) while those who expressed negative

emotions showed a decline in direct reports‟ ratings. These findings are important because they

demonstrate that immediate reactions to feedback are not merely transitory mood states without

relevance to subsequent behavior.

Several studies have examined the relationship between dispositional variables and

reactions to and behavior change after receiving multisource feedback. Smither, London, and

Richmond (2005) found that feedback recipients‟ emotional stability was positively related to a

psychologist‟s ratings (completed immediately after the leader received multisource feedback) of

the recipient‟s motivation to use the results from multisource feedback. They also found that

recipients‟ extraversion was positively related to requesting additional feedback and

conscientiousness was positively related to subsequently participating in developmental

activities. Dominick, Reilly, and Byrne (2004) found that conscientiousness and openness to

experience were positively related to performance improvement (i.e., enhanced effectiveness as a

team member) after receiving peer feedback from classmates (where ratings were collected from

different peers over a two-semester period). Heslin and Latham (2004) found that recipients

with high self-efficacy and a learning goal orientation subsequently improved more than other

managers. Atwater, Waldman, Atwater, and Cartier (2000) found that feedback recipients who

were low in organizational cynicism subsequently improved their performance more than others.

However, Walker, Atwater, Dominick, Brett, Smither, and Reilly (2006) described three studies

that found no evidence that personality (neuroticism, extraversion, openness to experience,

26

agreeableness, and conscientiousness) was related to improvement in multisource ratings over

time.

Feedback recipients who receive unfavorable feedback or who initially overrate

themselves tend to improve more than others (Atwater, Roush, & Fischthal, 1995; Johnson &

Ferstl, 1999; Smither, London, Vasilopoulos, Reilly, Millsap, & Salvemini, 1995; Walker &

Smither, 1999). In each of these studies, the improvement of feedback recipients who initially

overrated themselves or who initially received unfavorable feedback was greater than what

would be expected on the basis of statistical regression to the mean.

Not surprisingly, performance improvement is likely only for feedback recipients who

take appropriate action. For example, Smither, London, Flautt, Vargas, and Kucine (2003) found

that managers who worked with an executive coach were more likely than other managers to set

specific (rather than vague) goals, to solicit ideas for improvement from their supervisors, and to

improve in terms of subsequent direct report and supervisor ratings. However, the differences

between managers who worked with a coach and those who did not were small in magnitude

(albeit statistically significant). In a 5-year study of upward feedback, Walker & Smither (1999)

found that (a) managers who met with direct reports to discuss their upward feedback improved

more than other managers, and (b) managers improved more in years when they discussed the

previous year‟s feedback with direct reports than in years when they did not discuss the previous

year‟s feedback with direct reports. Smither, London, Reilly, Flautt, Vargas, and Kucine (2004)

also found that sharing multisource feedback and asking for suggestions from raters was

positively related to improvement over time. Hazucha, Hezlett, and Schneider (1993) found that

managers who participated in training programs and other development activities (e.g., receiving

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coaching and feedback, reviewing progress quarterly) after receiving multisource feedback were

more likely to improve than other managers.

Developing Employees

Although employee development can occur through formal training and education, in the

context of performance management more emphasis is usually placed on development through

ongoing coaching (usually from supervisors) and other less formal approaches to development

such as mentoring, task force assignments, and learning from challenging work (Zaleska & de

Menezes, 2007). London and Smither (1999a) presented a model of career-related continuous

learning, an individual-level process characterized by a self-initiated, discretionary, planned, and

proactive pattern of formal or informal activities that are sustained over time for the purpose of

applying or transporting knowledge for career development. Their model identifies

characteristics of the environment (e.g., value migration, deregulation, technology change),

employee (e.g., self-efficacy, openness to experience, learning orientation, proactivity), and

organization (e.g., learning resources and climate) that shape pre-learning, learning, and the

application of learning. London and Smither (1999b) have also noted the importance of self-

development, which involves employees seeking and using feedback, setting development goals,

engaging in developmental activities, and tracking progress on their own. They argue that

organizations can encourage self-development by providing employees with a clear

understanding of organizational goals and the implications of those for employee performance

and learning, holding both managers and employees accountable for continuous learning,

providing task- and behavior-focused feedback, and rewarding learning.

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Next, this section briefly reviews research about formal training. Then, because of its

importance in the context of performance management, research about coaching (including

executive coaching) is reviewed.

Formal Training

The value of formal organizational training has been widely documented. A

comprehensive meta-analysis of the impact of organizational training (Arthur, Bennett, Edens, &

Bell, 2003) found medium to large effect sizes for reaction (d = .60), learning (d= .63), behavior

(d = .62), and results (d = .62) criteria as well as positive effects for enhancing cognitive,

psychomotor, and interpersonal skills. Meta-analyses have demonstrated the positive effects of

training for management skills (Burke, & Day, 1986; Collins & Holton, 2004), team

performance (Salas, Nichols, & Driskell, 2007), and expatriate performance and adjustment

(Deshpande, Joseph, & Viswesvaran, 1994; Morris & Robie, 2001). The economic utility

(positive return on investment) of corporate training has also been demonstrated (Morrow,

Jarrett, & Rupinski, 1997). Despite the widespread positive effects usually associated with

formal training, some confidence intervals from meta-analyses include zero indicating that not

all training is effective.

Meta-analyses have demonstrated the efficacy of specific training methods such

overlearning (Driskell, Willis, & Copper, 1992), web-based instruction (Sitzmann, Kraiger,

Stewart, & Wisher, 2006), audiovisual, equipment simulators, lecture, discussion, programmed

instruction (Arthur et al., 2003), and behavior modeling (Taylor, Russ-Eft, & Chan, 2005).

Meta-analysis has also shown that some training methods can be especially valuable for certain

learners. For example, Callahan, Kiker, and Cross (2003) found that small group size and self-

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paced training, where learners can progress at their own pace, are especially helpful for older

learners.

Error management training (EMT, Frese, Brodbeck, Heinbokel, Mooser, Schleiffenbaum,

& Thiemann, 1991) encourages learners to make errors during training and to view errors as

opportunities to learn what does not work (e.g., errors are a natural part of the learning process;

the more errors you make, the more you learn). EMT facilitates learning (Heimbeck, Frese,

Sonnentag, & Keith, 2003) in part by reducing the learner‟s anxiety and in part by increasing the

learner‟s use of planning and monitoring (Keith & Frese, 2005). A meta-analysis by Keith and

Frese (2008) found that, relative to error avoidant training or exploratory training without error

encouragement, EMT was more effective (d = 0.44) for post-training transfer performance (but

not for within-training performance). It was especially effective for performance on adaptive

tasks (i.e., novel problems that require the development of new solutions) relative to analogical

tasks (that are similar or analogous to the training task). Both active exploration (where

participants are not guided to correct solutions but work independently to find solutions on their

own) and error encouragement contribute to the effectiveness of EMT. Also, there is evidence

that an organizational error management culture (which consists of norms and common practices

that involve communicating about errors, sharing error knowledge, helping in error situations,

and quickly detecting and handling errors) is positively related to organizational goal

achievement and indicators of firm economic performance (van Dyck, Frese, Baer, & Sonnentag,

2005).

Bell and Kozlowski (2008) recently found that active learning interventions (such as error

encouragement framing and exploratory learning) influence the nature, quality, and focus of self-

regulatory activity. Compared with alternative, more traditional interventions (such as error

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avoidance framing or proceduralized instruction), these active learning interventions led to better

adaptive transfer (although they do not necessarily lead to better performance during training).

Self-management training has also been shown to increase performance (as well as self-

efficacy; Frayne & Geringer, 2000) and decrease absenteeism (Frayne & Latham, 1987; Latham

& Frayne, 1989). It involves (1) identifying the behaviors to modify, (2) establishing goals for

those behaviors, (3) maintaining a record of progress toward goal attainment, (4) establishing

self-rewards and self-punishments for performance relative to goals, (5) identifying high-risk

situations that might frustrate goal attainment, and (6) preparing a written contract with oneself

that lists goals, plans, contingencies, and so on.

On-the-Job Coaching

The shift in emphasis from performance appraisal (a discrete event) to performance

management (a continuous process) has focused attention on the important role of coaching in

employee performance and development (Latham et al., 2005). Over 60 years ago, Lewis

referred to coaching as “really just good supervision” (1947, p. 316). And being an effective

coach continues to be viewed as an essential feature of effective management (Hamlin, Ellinger,

& Beattie, 2006). Employees believe that behaviors associated with effective coaching include

communicating clear performance expectations, providing regular feedback, observing employee

performance, developing self-improvement plans, and building a warm relationship (Graham,

Wedman, & Gavin-Kester, 1993). Gittell (2001) found that narrow spans of control create the

opportunity for supervisors to provide more coaching and feedback. Supervisors with narrow

spans of control also had more opportunity to work side-by-side with their group members,

which in turn reduced the informational and social distance between the supervisor and the group

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and led to shared goals. Shared goals made the group more receptive to coaching and feedback

from the supervisor and reduced the need for supervisory monitoring.

There is some evidence that coaching skills can be developed. For example, a program

designed to enhance managers‟ coaching skills had a positive effect on five of eight target

behaviors (Graham et al., 1993). But managers are unlikely to provide coaching if they believe

that employee performance cannot be improved. Heslin and colleagues (Heslin, Latham, &

VandeWalle, 2005) examined managers‟ implicit person theories and found that managers who

held incremental beliefs (i.e., ability is malleable and can therefore be developed with effort)

were more likely than managers who held entity beliefs (i.e., ability is fixed, innate, and

unalterable) to recognize both improvements and declines in employee performance. In a

separate study, these authors used a 90-minute workshop based on self-persuasion techniques

(Aronson, 1999) to help participants who initially held entity beliefs to acquire incremental

beliefs and to sustain those beliefs over a 6-week period. This change led to greater

acknowledgement of improvement in employee performance than was exhibited by entity

theorists in a placebo control group. They also found that inducing incremental beliefs increased

entity theorist managers' willingness to coach a poor performing employee, as well as the

quantity and quality of their performance improvement suggestions (Heslin, VandeWalle, &

Latham, 2006; Heslin &VandeWalle, 2008).

A number of studies have found evidence supporting the value of coaching. For

example, a survey by Ellinger, Ellinger, and Keller (2003) found that supervisory coaching

behaviors (e.g., providing and asking for feedback, helping employees think through issues by

asking questions rather than providing solutions, setting expectations, providing resources) were

positively related to employee job satisfaction and performance. Edmondson (1999) found that

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coaching by the team leader was positively related to the team‟s psychological safety, which in

turn was positively related to its learning behavior. Cannon and Edmondson (2001) found that

coaching on the part of the manager can help a group overcome the interpersonal and

organizational barriers to discussing errors, problems and conflict. Konczak, Stelly, and Trusty

(2000) found that coaching for innovative performance (e.g., encouraging employees to try out

new ideas even if there is a chance they might not succeed) was positively associated with

employee job satisfaction and organizational commitment. Bennett (1987) found that the

addition of on-site coaching to other training elements (theory, demonstration, practice, and

feedback) increased the utilization of newly learned skills and strategies in classroom instruction.

Rappe and Zwick (2007), in a quasi-experiment, showed that a combination of leadership

workshops and individual coaching by an internal consultant had positive effects on self-reported

leadership competencies of first-line managers. Acosta-Amad and Brethower (1992) found that

a combination of on-the-job coaching, training, and feedback improved the note-writing

performance of staff members in a psychiatric hospital. In a quasi-experimental study,

Gyllensten and Palmer (2005) found that recipients perceived coaching (provided by an internal

coach with the goal of reducing anxiety and stress) to be effective, but pre-post differences in

anxiety and stress among those who were coached did not differ significantly from those who

were not coached. Scandura (1992) found that career coaching by mentors was positively related

to managers‟ promotion rate.

More recent theoretical and empirical work suggests that coaching is likely to be

effective in some settings but not in others. For example, Hackman and Wageman‟s (2005)

theory of team coaching proposes that coaching interventions that focus on team effort, strategy,

and knowledge and skill will facilitate team effectiveness more than interventions that focus on

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members‟ interpersonal relationships. Also, they suggest that timing is important in determining

the optimal type of coaching such that motivational coaching will be most helpful at the

beginning of a performance period, consultative coaching will be most helpful at the midpoint of

a performance period, and educational coaching (i.e., helping the team capture what can be

learned from the collective work just completed) will be most helpful after performance

activities have been completed.

In a study of external leadership of self-managing teams, Morgeson (2005) found that

supportive coaching (reinforcing the team for its self-management behaviors and thereby

fostering a sense of competence and independence in the team without becoming directly

involved in the team‟s task work) was positively related to perceptions of leader effectiveness,

however active coaching (i.e., becoming directly involved in helping the team perform its work)

and leader sense making (i.e., the leader interpreting events for the team) were negatively related

to satisfaction with leadership but positively related to perceptions of leader effectiveness when

disruptive events occur.

Wageman (2001) found that positive coaching (e.g., providing informal rewards and

other cues that the group-as-a-whole is responsible for managing itself, teaching the group to use

a problem-solving process; facilitating problem-solving discussions) was positively related to

team self-management and the quality of team process, but not to team performance. Negative

coaching (e.g., intervening in the task, dealing directly with a team's customer without involving

the team, identifying the team's problems) was negatively related to team self-management and

member satisfaction, but not to team performance. She also found that effective coaching helps

well-designed teams more than poorly designed teams, and that ineffective coaching hurts poorly

designed teams more than well- designed teams.

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Executive Coaching

Executive coaching has been defined as a short- to medium-term relationship between an

executive and a consultant with the purpose of improving the executive‟s work effectiveness

(Feldman & Lankau, 2005). Hall, Otazo, and Hollenbeck (1999) state that executive coaching is

“a practical, goal-focused form of personal one-to-one learning for busy executives. It may be

used to improve performance, to improve or develop executive behaviors, to work through

organizational issues, to enhance a career, or to prevent derailment.” Executive coaching can

take a number of different forms. Some executives use coaching to learn specific skills, others to

improve performance on the job or to prepare for advancement in business or professional life,

and still others to support broader purposes, such as an executive's agenda for major

organizational change (Witherspoon & White, 1996). Feldman and Lankau (2005) note that

executive coaches differ from advisers (who share their business or technical expertise), career

counselors (who help match executives to jobs in the external labor market), mentors (usually

more experienced employees who help protégés), and therapists (who help employees with

emotional or behavioral problems), and that, because coaching is unregulated, anyone can

describe himself r herself as an executive coach.

Generally, executive coaching includes several stages such as establishing the coaching

relationship, data gathering (about the executive and the organization), feedback (presenting the

executive with the results of the data gathered from interviews, psychological assessments,

multi-source feedback, etc.), goal setting, periodic coaching sessions, and evaluation (to

determine progress toward the goals of coaching) (Feldman & Lankau, 2005; Smither & Reilly,

2001).

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Latham (2007) has argued that the practice of coaching needs to be explicitly linked to

well-established psychological frameworks (e.g., implicit person theory, goal setting,

sociocognitive theories) to create an evidence-based approach to coaching. To date,

psychologists have approached executive coaching from a variety of conceptual frameworks

including social psychology, positive psychology, rational-emotive therapy, cognitive-behavior

therapy, emotional intelligence, psychoanalysis, family therapy, hypnosis, person-centered,

systems-oriented, psychodynamic, multi-modal therapy, and even eye movement desensitization

and reprocessing (e.g., Biswas-Diener & Dean, 2007; Feldman & Lankau, 2005; Peltier, 2001;

Smither & Reilly, 2001).

Coaching clients want coaches to have graduate training in psychology; experience in (or

an understanding of) business; listening skills, and an established reputation (Wasylyshyn, 2003).

In a survey of 428 executive coaches, Bono, Purvanova, Towler, and Peterson (in press)

compared the practices (e.g., approaches to coaching, use of assessment tools) of psychologist

and non-psychologist coaches, as well as the practices of coaches from various psychological

disciplines (e.g., counseling, clinical, and industrial/organizational). They found (a) the

differences between psychologist and non-psychologists were generally small (d =.26), and (b)

as many differences between psychologists of differing disciplines as between psychologist and

non-psychologist coaches. It is possible that psychological training is valuable in some

circumstances but not in others. For example, Kilburg (2004) suggests that psychological

interventions might be especially relevant when a manager continues to under-perform despite

being motivated to do better or when a manager lacks sufficient knowledge or skills to cope with

a challenging situation or problem or when the manager‟s interpersonal relationships limit his or

her ability to perform the job or advance in the organization.

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Although human resource professionals who sponsor executive coaching have positive

perceptions of its benefits (Dagley, 2006), the vast majority of articles about executive coaching

rely on case studies or vignettes as illustrations or sources of evidence and only a small number

of empirical studies have examined the impact of executive coaching (Feldman & Lankau,

2005). Of these, many have relied on self-reports and surveys of coaching recipients to evaluate

the impact of coaching. These studies have found that coaching recipients perceive coaching as

valuable and believe they benefitted from it (e.g., progress toward goals, sustained behavior

change) (Evers, Brouwers, & Tomic, 2006; Feggetter, 2007; Hall, Otazo, & Hollenbeck, 1999;

Hollenbeck & McCall, 1999; Kombarakaran, Yang, Baker, & Fernandes, 2008; Wasylyshyn,

2003; Wasylyshyn, Gronsky, & Hass, 2006). McGovern, Lindemann, Vergara, Murphy, Barker,

and Warrenfeltz (2001) examined the impact of executive coaching on 100 executives from 56

organizations. Coaching programs generally ranged from 6 to 12 months in duration. Based on

interviews, they found that 86% of participants and 74% of stakeholders (immediate supervisors

or HR representatives) indicated they were very satisfied or extremely satisfied with the

coaching process. Participants estimated that the return on coaching was nearly 5.7 times the

investment in coaching. However, these results relied on executives‟ estimates of impact, as

contrasted with input from other stakeholders.

A small number of studies have relied on somewhat more objective indicators (relative to

self-reports). Olivero, Bane, and Kopelman (1997) examined the effects of executive coaching

in a public sector agency where managers participated in a three-day management development

program and then worked with an internal executive coach for eight weeks. The authors found

that both the management development program and coaching increased productivity with

executive coaching resulting in a significantly greater gain compared to the management

37

development program alone. Luthans and Peterson (2003) found that a combination of 360-

degree feedback and coaching (focused on enhanced self-awareness and behavioral

management) was associated with improvements in coworkers‟ ratings of the feedback recipients

(managers) and improvements in job satisfaction, organizational commitment, and turnover

intentions for the managers and their employees. However there was no control group and the

design of the study also did not allow the authors to disentangle the effects of coaching from

those of the 360-deree feedback. Smither, London, Flautt, Vargas, and Kucine (2003) used a

quasi-experimental design that examines 1,361 managers who received multisource feedback;

404 of those managers worked with an executive coach to review their feedback and set goals.

One year later, managers who worked with an executive coach were more likely than other

managers to have (a) set specific (rather than vague) goals (d = .16), (b) solicited ideas for

improvement from their supervisors (d = .36), and (c) improved more in terms of direct report

and supervisor ratings (d = .17). Although executive coaching had a statistically significant and

positive effect, the effects sizes were quite small. Bowles, Cunningham, De La Rosa, and Picano

(2007) found that middle (but not executive-level) managers who volunteered to receive 8 hours

of formal training followed by, on average, 6 to 7 hours of coaching outperformed (e.g.,

achievement of quotas) managers who had not received the training and coaching. Because the

participants were volunteers and the coaching was combined with formal training, the impact of

coaching on performance remains uncertain. Bowles and Picano (2006) found that managers

who more frequently applied coaching advice (delivered by an external coach via telephone

conference calls) reported more work satisfaction but coaching was not related to productivity.

Kampa-Kokesch (2001) compared ratings of transformational and transactional leadership of

executives in the early versus late stages of coaching and found only one significant difference

38

(which was related to a transactional leadership scale). Support from an external (to the team)

coach has been shown to predict the emergence of shared leadership in teams (whereby

leadership is distributed among team members rather than focused on a single designated leader;

Carson, Tesluk, & Marrone, 2007). Sue-Chan and Latham (2004) found that MBA students

coached by an external coach showed more teamwork behavior and higher grades than those

coached by peers, and that an external coach was perceived as being more credible than peer

coaches. In sum, the limited research indicates that sponsors and recipients have favorable

reactions to coaching and some positive benefits have been found. However, due to limitations

in the design of most studies, it is difficult to make firm conclusions about the impact of

executive coaching on performance.

Evaluating Performance

Most performance evaluation or appraisal processes ask the supervisor to rate the

effectiveness of the employee on several dimensions of performance and to provide a rating of

overall performance (although sometimes rankings rather than ratings are used). These ratings

are often linked to administrative decisions such as salary increases, promotions, or terminations.

However, evidence indicates that employees who perceive the use of performance appraisal to be

developmental are more satisfied with the appraisal and the supervisor even after accounting for

the effects of justice perceptions and the appraisal rating (Boswell & Boudreau, 2000).

Research on performance appraisal has been flourishing for nearly a century. Because

objective measures of performance are not available for many (if not most) jobs, subjective (e.g.,

supervisor) ratings play a central role in evaluating employee performance. Even when objective

measures are available, research has repeatedly shown that ratings of performance are only

modestly related to objective measures of performance (Bommer, Johnson, Rich, Podsakoff, &

39

Mackenzie, 1995; Cascio & Valenzi, 1978; Heneman, 1986; Kirchner, 1960; Seashore, Indik, &

Georgopoulos, 1960). Although this likely reflects limitations associated with ratings, it also

likely reflects problems with objective measures such as criterion deficiency and contamination.

Wexley and Klimoski (1984) suggested that there is no „true‟ job performance. Instead, ratings

and objective measures (e.g., productivity) are different indicators that tap different aspects of

performance.

Thorndike‟s classic paper on rating errors (1920) led to a longstanding focus on how to

reduce such errors under the assumption that less rating error would lead to more rating

accuracy. Much attention was centered on developing rating formats that might reduce rating

errors. Numerous formats were developed including forced choice (Sisson, 1948), critical

incidents (Flanagan, 1954), behaviorally anchored rating scales (Smith & Kendall, 1963), mixed

standard scales (Blanz & Ghiselli, 1972), behavioral observation scales (Latham, Fay, & Saari,

1979; Latham & Wexley, 1977), and performance distribution assessment (Kane, 1982). At the

same time, rater training programs focused on reducing rater errors such as halo and first

impressions (Latham, Wexley, & Pursell, 1975).

An influential review by Landy and Farr (1980) noted that rating formats or scales had

little if any effect on reducing rating errors or increasing agreement among raters. (Although it

should be noted that rating format can have other effects. For example, raters generally prefer

behavioral observation scales relative to behavioral expectation scales or trait scales and

behavioral observation scales, relative to graphic rating scales, yield higher levels of goal clarity,

acceptance, and commitment; Tziner & Kopelman, 1988; Wiersma, van den Berg, & Latham,

1995). Landy and Farr (1980) suggested that it made more sense to view the rater (rather than

the rating scale) as the „instrument‟ and that research should therefore focus on the rater. This

40

led to cognitive approaches to (or models of) performance appraisal (see DeNisi, 1996, for a

summary). Papers by DeCotiis and Petit (1978), Feldman (1981), Ilgen and Feldman (1983), and

DeNisi, Cafferty, and Meglino (1984) all focused on raters‟ cognitive processes (rather than

rating formats). These models borrowed heavily from research on person perception and social

cognition that was taking place in social psychology. Moreover, these models looked at how

raters recognize, attend to, and observe employee behavior (or other information related to

employee performance), represent, organize, and store this information in memory, retrieve the

information from memory, and integrate the information to form a judgment about or evaluation

of the employee. This research illustrated the important role that categories and schemas play in

automatic processing (where little cognitive energy is expended) and showed that controlled

processing (which requires more deliberate cognitive effort) occurs only when information is

acquired about an employee that is quite inconsistent with the category or schema to which the

employee has already been assigned by the rater. It also showed how categories and schemas

shape subsequent information processing (e.g., what raters attend to and recall) and ratings of

performance.

More recently, conceptual models have emphasized the important role of context and

goals in appraisals (Murphy & Cleveland, 1991; Murphy & Cleveland, 1995). Contextual

factors include proximal variables that directly affect the rater such as the nature of the

relationship between the supervisor and employee (e.g., close and informal versus distant and

formal), the nature of the job, time constraints on the rater, and the consequences of ratings.

They also include distal variables that influence the rater less directly such as the organization‟s

culture and values.

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There are numerous examples of contextual effects on ratings. For example, a meta-

analysis by Jawahar and Williams (1997) found that the purpose of the appraisal influences

leniency in ratings such that appraisals obtained for administrative purposes (e.g., to influence

pay raises or promotions) were about one-third of a standard deviation higher than those obtained

for employee development or research purposes, especially when the ratings were made by

practicing managers in real-world settings. Trust in the appraisal process (whether a rater

believes that others in the organization will provide fair and accurate appraisals) also affects

leniency in ratings (Bernardin & Orban, 1990). Raters high in agreeableness provide more

lenient ratings when they expect to have a face-to-face meeting with the employee, but this effect

is attenuated when using a behavior checklist rather than a graphic rating scale (Yun, Donahue,

Dudley, & McFarland, 2005). Similarly, raters accountable to others with authority or higher

status provide more accurate ratings compared with raters who are accountable to a lower status

audience and raters who do not have to justify their ratings (Mero, Guidice, & Brownlee, 2007).

In a lab experiment, Shore, Adams, and Tashchian (1998) showed that self-appraisals can

influence the supervisor‟s appraisal of the employee such that supervisors‟ ratings are higher

when they receive a favorable (rather than unfavorable) self-appraisal from the employee.

Prior impressions of the ratee or receiving indirect information (e.g., from others) about

the ratee‟s performance also influence evaluations (Buda, Reilly, & Smither, 1991; Smither,

Reilly, & Buda, 1988; Reilly, Smither, Warech, & Reilly, 1998). For example, individual raters

told that a group had been judged to be very good (before observing the group), subsequently

recalled more effective behaviors (including behaviors that had not occurred) and fewer

ineffective behaviors than raters told that the (same) group had been judged to be very poor

(Martell & Leavitt, 2002). That is, knowledge of the target‟s performance serves as a cue that

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leads raters to recall cue-consistent attributes (effective or ineffective behaviors) as having

occurred (even if they had not). However, Salvemini, Reilly, and Smither (1993) showed that

motivating raters (by offering an incentive to be accurate) eliminated this bias, and Martell and

Leavitt (2002) demonstrated that this bias can be eliminated when ratings are completed by a

group (rather than by individuals).

Moreover, the rater‟s goal need not necessarily be to provide an accurate rating of the

employee‟s performance. For example, Murphy and Cleveland (1991, 1995) note that judgments

(the rater‟s private view) and ratings (the rater‟s public statement) are not identical. Because

ratings do not necessarily reflect the rater‟s judgments, a supervisor (or other raters) might hold

an accurate view of an employee‟s performance but deliberately provide an inaccurate rating.

For example, a supervisor might provide a rating that is more favorable than the supervisor‟s

judgment of the employee, perhaps to avoid an unpleasant or difficult conversation or to help the

employee obtain a higher salary increase. Ratings (as contrasted with judgments) are especially

likely to be shaped by political considerations (Longnecker, Gioia, & Sims, 1987). For example,

because a poor rating might damage the supervisor‟s relationship with an employee, the

supervisor might provide an inaccurate (more favorable) rating and thereby create a climate

where the two can work together more comfortably going forward. Or a supervisor might

provide a poor rating (that is lower than the supervisor‟s judgment of the employee‟s

performance) to teach a disruptive or uncooperative employee a lesson. A scale to measure

perceptions of the extent to which performance appraisals are affected by organizational politics

has been developed by Tziner, Latham, Price, and Haccoun (1996).

Harris (1994) noted that much of the research concerning performance appraisal had

focused on the rater‟s ability to provide accurate ratings (e.g., by providing raters with training

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and behaviorally-focused rating formats) but little attention had been directed to the rater‟s

motivation in the appraisal process. He argued that there are three determinants of rater

motivation: rewards (e.g., whether providing accurate ratings or feedback to employees will be

rewarded by the organization or will indirectly affect the rater‟s rewards by leading to improved

employee performance), negative consequences (e.g., whether ratings or feedback might

demoralize the employee or damage the manager-employee relationship), and impression

management (e.g., adhering to organizational norms or wanting to give favorable ratings so that

the manager is perceived by others as having an effective work group). Harris argued that

several situational factors will enhance rater motivation. These include accountability (having to

justify one‟s ratings to others), interdependence (when the rater‟s outcomes and rewards are

highly dependent on the employee‟s performance), trust in the appraisal system (believing that

others will provide fair, rather than lenient, ratings of their employees), and ease of use (appraisal

forms that are not too difficult or time-consuming to complete). Harris also emphasized that

rater motivation can affect all stages of the performance appraisal process including observing

employee performance, storing the observed information in long-term memory, retrieving

complete information, integrating this information, rating the employee, and providing feedback.

Moreover, motivated raters are more likely to use deliberate or controlled information processing

strategies rather than quick, heuristic-based, or automatic information processing strategies at

each of these stages.

Problems with the concept of rater errors (although long noted by some) have become

more widely acknowledged. For example, covariance among different performance dimensions

or a small intra-employee standard deviation of ratings across dimensions were often viewed as

an indicator of halo error. Similarly, when favorable ratings were given to several employees,

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this was viewed as an indicator of leniency error. Of course, in some instances, employees might

perform effectively (or ineffectively) across several dimensions (or a group of employees might

all be especially effective performers). In such instances, rater „errors‟ might actually be

associated with more accurate ratings (Cooper, 1981a, 1981b). Several studies where true scores

were known (e.g., by using expert ratings of videotaped performance) found paradoxically

positive correlations between error (halo) and accuracy (e.g., Borman, 1977, 1979). Hence,

research attention turned away from rater errors and toward enhancing rater accuracy. This was

accompanied by a shift in rater training to increase accuracy rather than reduce errors (Bernardin

& Buckley, 1981; Bernardin & Pence, 1980; Hauenstein, 1998). Such training (often referred to

as frame of reference training) generally involves familiarizing raters with the definitions and

behavioral indicators of each performance dimension, providing opportunities to complete

practice ratings (using either written vignettes or videos to present the performance examples),

and delivering feedback concerning the accuracy of the practice ratings (by comparing them with

target ratings that represent the organization‟s estimate of the effectiveness levels demonstrated

in the performance examples). A cumulative research review by Woehr and Huffcutt (1994)

showed that frame of reference training is an effective approach to increase rating accuracy.

Viswesvaran (2001) reviewed criteria that can be considered to determine the quality of

performance appraisals. These include discriminability across individuals, practicality,

acceptability (e.g., to users), reliability, comprehensiveness (i.e., the absence of criterion

deficiency), and construct validity (i.e., job-relatedness and the absence of criterion

contamination). Despite the importance of reliability, the inter-rater reliability of performance

ratings is notoriously low. A meta-analysis by Viswesvaran, Ones, and Schmidt (1996) found

that the inter-rater reliability of supervisor ratings of overall job performance was .52 (for peer

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ratings it was .42). Rothstein (1990) found that inter-rater reliability is positively related to

opportunity to observe the ratee (especially over the first 12 months), however the asymptotic

value of reliability was only .55. It is important to note that different raters often observe the

employee on different occasions and in different settings, therefore lack of agreement between

raters does not necessarily indicate that either or both raters are in error.

Murphy and Cleveland (1995) have questioned whether the benefits of performance

appraisal outweigh the costs. And, despite decades of research, Murphy (2008) argues that the

relationship between ratings of job performance and job performance remains weak or uncertain.

He states that some models of performance ratings assume that the difference between job

performance and ratings is simply obscured by measurement error and that the variance in

ratings can be partitioned into true score and error variance (with the corresponding

recommendation that, when examining the correlates of ratings, problems with ratings can be

remedied by correcting for attenuation due to unreliability). But Murphy argues that it is

unreasonable to assume that, after random measurement error is removed from ratings, the

portion that is left is simply job performance. Instead, he states that differences between job

performance and ratings are not “inexplicable, idiosyncratic errors on the part of raters, but rather

are the result of a combination of systematic and random factors in the environment in which

ratings are obtained” (p. 155). (Many of these factors are described above.) Ultimately, Murphy

(2008) concludes that organizations need to create an environment where “raters have: (a)

incentives, tools and opportunities to observe and recall ratees‟ job performance, (b) incentives

to provide ratings that faithfully reflect the rater‟s evaluation of each ratee‟s performance, and (c)

protection against the negative consequences of giving honest ratings” (p. 157). There is no easy

practical solution to the problems associated with ratings. One approach used by many

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organizations is to require supervisors to share, discuss, and justify their ratings of employees

with others (e.g., the supervisor‟s manager or a panel of peers). This approach might help

calibrate ratings made by different supervisors and lessen unjustifiable leniency in ratings but as

Murphy (2008) notes, it also make raters more vulnerable to social influence effects (e.g., norms

about rating distributions) that might actually reduce the accuracy of ratings in some instances.

Forced Distributions

During the past several years, perhaps no other aspect of performance management has

garnered as much attention in the popular press as the use of forced distributions or rankings

(Dominick, 2009). In absolute rating systems (such as behaviorally anchored rating scales and

behavioral observation scales), raters make judgments about the extent to which each employee

displays a variety of job-related behaviors; all employees are evaluated relative to the same

behaviors (standards) and it is therefore possible that all employees could receive the same

rating. In contrast, relative rating systems, which include forced ranking or distribution systems,

require raters to evaluate employees relative to one another, determining which employees are

best, next best, and so on. One approach to forced distributions uses an approximate normal

distribution to slot employees into a bell-curve shaped distribution (e.g., 10% in the top category,

15% in the next category, 50% in the middle category, 15% in the next category, and 10% in the

bottom category). More commonly, most employees are placed into one of the top three

categories of a five-point rating scale (e.g., 10% in the top category, 20% in the next category,

60% in the middle category, and the remaining 10 % in the bottom two categories).

Advocates argue that forced distribution systems reduce or eliminate artificially inflated

ratings (Taylor & Wherry, 1951), thereby enabling organizations to identify and adequately

reward top performers while also holding poor performers accountable. They also argue that

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forced distributions are fair to poor performers because the system lets such employees know

where they stand so they have an opportunity to do something about it (perhaps by moving to

other organizations or jobs where they can succeed). Critics argue that forced distributions are as

susceptible to favoritism, manipulation and organizational politics as any other rating process

and that they are unreasonable when the number of employees in the rating group is small.

Concerns have also been raised about the effects of forced distribution systems on perceived

fairness and employee morale (McBriarty, 1988) as well as legal compliance (Dominick, 2009).

Several features of forced distribution systems appear especially related to the controversy

concerning their use. These include the consequences of being rated in the lowest categories

(e.g., will such employees be terminated?), the difference in rewards received by employees in

different categories, and the number of employees in the rating group.

Two meta-analyses indicate that relative rating formats (which include forced

distributions) appear to offer advantages compared to absolute rating formats. Heneman (1986)

found that the correlation between supervisory ratings and results-oriented measures of

performance was higher for relative rating formats than for absolute rating formats. Nathan and

Alexander (1988) found that validity coefficients for clerical ability tests were higher when

supervisory rankings rather than supervisory ratings were used as criteria.

In a policy-capturing study, Blume, Baldwin, and Rubin (2007) found that more

favorable reactions to forced distribution rating systems were associated with the absence of

severe consequences for poorly ranked employees, having a reasonably large rating (comparison)

group, and a process that ensured employees receive frequent feedback. In two studies

examining reactions to forced distribution rating systems, Schleicher, Bull and Green (2007)

found that such systems were less likely to be perceived as fair and more likely to be seen as

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difficult when there were administrative consequences (e.g., termination, compensation, and so

on) and when there was little variability in performance among those being ranked. They also

found that a forced distribution system was perceived as less fair than an absolute rating format.

Finally, it has been argued that forced distribution systems are better suited to some

organizational cultures (e.g., highly results-oriented where success does not depend heavily on

teamwork) than others (Guralnik, Rozmarin, & So, 2004).

One recurring concern raised about forced distribution ratings systems is their potential to

create competition rather than collaboration among employees (Guralnik, Rozmarin, & So, 2004;

Hymowitz, 2001, McBriarty, 1988). Supporting this concern, Garcia and colleagues (Garcia,

Tor & Gonzalez, 2006; Garcia & Tor, 2007) have shown that rivals near the top of a distribution

were less likely to cooperate when doing so had the potential to advance the other person‟s

standing.

In a survey of human resource professionals, Lawler (2003) found that, compared to

those not using forced distributions, those using forced distributions judged their systems as

better able to differentiate between levels of performance (e.g. to identify and reward top talent,

identify and manage out poor performers), but also judged their systems as less effective at

developing talent and less effective overall.

Rewarding Performance

Performance management systems seek to link rewards (e.g., money, recognition) to

performance. Indeed, from a practical perspective, performance evaluations are often conducted,

at least in part, because they serve as the basis for decisions about compensation. Yet a recent

review by Rynes, Gerhart, and Parks (2005) notes that relatively little psychological research has

examined the consequences of linking pay to performance (although such research has occurred

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more often in other disciplines such as management, economics, and finance). They argue that

three motivation theories have had the perhaps unintended effect of diminishing research interest

in the linkage between performance evaluation and pay for performance. For example,

Maslow‟s need hierarchy theory (1943) acknowledged the importance of lower-level

physiological and safety needs (which presumably can be satisfied by money) but emphasized

the importance of higher-order needs such as love, esteem, and self-actualization (which

presumably could be better met through engagement in meaningful work than by money).

Herzberg‟s motivation-hygiene theory (Herzberg, Mausner, Peterson, & Capwell, 1957) viewed

satisfaction and dissatisfaction as two distinct constructs and suggested that money was more

likely to play a role in creating or reducing dissatisfaction than in increasing satisfaction. Deci

and Ryan‟s cognitive evaluation theory (1985) has been interpreted by some (albeit inaccurately)

to mean that any emphasis on external rewards (such as pay) will inevitably diminish intrinsic

interest in the work itself. Collectively, these three theories can be seen as indicating that money

plays only a small or perhaps negative role in motivation. Rynes et al. (2005) show that the

small role of money as a motivator in Maslow‟s and Herzberg‟s theories is not supported by

empirical evidence. They also note that evidence from Deci and Ryan‟s theory is based almost

entirely on research with children and college students in laboratory settings rather than with

adults in real-world work settings.

Types of Pay for Performance Plans

Heneman and Gresham (1998) note that pay for performance plans can focus on

individual performance (e.g., merit pay, skill-based pay, piece rates, sales commissions, employee

suggestion systems), team performance (e.g., team incentives, team recognition) or organizational

performance (e.g., gainsharing, profit sharing, stock ownership).

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At the individual level, merit pay plans involve linking pay increases to subjective (usually

the supervisor‟s) ratings of the employee‟s performance in the previous time period. Merit plans

can also reward behaviors related to effective teamwork (e.g., collaboration, communication,

conflict resolution) to encourage cooperation and limit competition among team members. In

skill-based pay, increases in compensation are based on mastery (usually defined via certification

by supervisors, trainers, or peers) of carefully defined skill sets. Skill-based pay makes sense when

its higher costs (for training and compensation) are outweighed by the advantages of a more

flexible work force (Heneman & Gresham, 1998). Employee suggestion systems provide rewards

to individual employees for suggestions that lead to cost savings or enhance revenues. One

potential downside of individual-level pay for performance is that employees might see little value

in cooperating with coworkers (which can create problems when cooperation would benefit the

group or organization as a whole).

At the team level, team incentives can be used in situations where (a) the team produces an

identifiable output, and (b) it is difficult or impossible to measure the contribution of individual

team members. Usually the incentive is divided equally among team members. Team recognition

plans provide monetary or nonmonetary rewards to teams that identify more efficient methods to

produce a product or deliver service. One downside to pay for performance at the team level is

what has been referred to as social loafing or free riding, where some employees limit their efforts

when they believe that their individual contributions cannot or will not be assessed and others on

the team will work very hard to ensure the team‟s success (Albanese & Van Fleet, 1985; Cooper,

Dyck, & Frohlich, 1992; Heneman & von Hippel, 1995; Kidwell & Bennett, 1993; Shepperd,

1993). When individual contributions to team success can be assessed, then team rewards can be

distributed proportional to those contributions. Consistent with what would be expected based on

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social loafing or free rider research, the size of the group moderates the effectiveness of group pay

plans, with a larger impact occurring in smaller firms (Rynes et al. 2005).

At the facility or organization level, gainsharing plans provide rewards for cost (or time)

savings or revenue enhancement. Heneman and Gresham (1998) note that an attractive feature of

gainsharing plans is that they pay for themselves because rewards are not distributed until costs are

reduced or revenue is enhanced. Gainsharing plans generally use joint committees of employees

and managers who solicit, screen, and help implement suggestions from employees. The cost

savings or increased revenues are split between employees (with each employee receiving an equal

amount) and management (who can reinvest the money). Sometimes, each employee receiving the

same amount (reward) can create resentment among employees who think their contributions were

greater than the contributions of other employees.

Profit sharing plans are based on the financial performance of the entire organization (e.g.,

as measured by a predetermined metric such as net income, return on assets, economic value

added, earnings per share, etc.) and can provide employees with the associated reward soon after

the amount of profit has been determined or can defer payment until the employee retires (or a

combination of both). Stock ownership and stock options can also link pay to organizational

performance. One issue associated with all organization-level pay for performance plans has been

referred to as the „line of sight‟ problem where employees see little connection between their

performance and the performance of the organization as a whole (Heneman & Gresham, 1998).

This is especially likely to be a problem when poor organizational performance and hence low plan

payouts are perceived as being due to factors beyond employees‟ control such as poor decisions of

executives (Rynes et al., 2005).

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Heneman and Gresham also argue that pay for performance plans should be matched to

business objectives. For example, skill-based pay plans would be a good fit for employee

development objectives, individual plans (e.g., piece rate) and gainsharing plans would be a good

fit for productivity (e.g., revenue enhancement or cost reduction) objectives, team recognition and

team incentives would be a good fit for teamwork objectives, and profit sharing would be a good

fit for profit objectives.

Many organizations link pay to performance at multiple levels (e.g., merit pay, team

incentives or recognition, and profit sharing) in an attempt retain the advantages of each approach

while minimizing its potential negative consequences (Rynes et al., 2005). Unfortunately, little

research exists concerning the consequences of combining several approaches (for exceptions, see

Wageman, 1995, and Crown & Rosse, 1995).

Research on Pay for Performance

In a survey of Fortune 500 companies, Lawler (2003) found that respondents thought that

performance management systems are more effective when there is a strong connection between

appraisals and rewards (salary increases, bonuses, stock awards). Research generally supports this

belief. However, exempt employees tend to be more supportive of performance based pay than

nonexempt employees who are more supportive of pay based on seniority and cost of living

(Heneman, 1992).

Generally, individual-level plans (e.g., piece rate, sales commissions), have larger effects

on productivity than unit-level plans (such as gainsharing) which in turn have a greater impact than

corporate-wide plans such as profit sharing (Heneman and Gresham, 1998; Rynes et al., 2005). In

an early meta-analysis, Locke and colleagues (Locke, Feren, McCaleb, Shaw, & Denny, 1980)

concluded that individual pay incentives increased performance by an average of 30%, and had a

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greater impact than goal setting, job enrichment, or employee participation. A meta-analysis by

Judiesch (1995) concluded that the increase in output due to individual incentive compensation

systems is on average 33 percent. A meta-analysis by Guzzo, Jette, and Katzell (1985) also

found that financial incentives had a positive effect on performance (d = .57). Finally a meta-

analysis by Jenkins, Mitra, Gupta, and Shaw (1998) found the correlation between financial

incentives and performance quantity was .34, with field experiments (.48) yielding effects twice

as large as those found in lab experiments (.24), however financial incentives were not related to

performance quality.

Unfortunately, very little research exists concerning the impact of merit pay (the most

popular method of linking pay to performance) on subsequent behavior and performance, although

there is a good deal of research on attitudinal reactions to merit pay (Heneman & Gresham, 1998;

Heneman & Werner, 2005; Rynes et al. 2005). A detailed research review by Heneman and

Werner (2005) found that merit pay was usually but not always associated with positive employee

attitudes (e.g., satisfaction with pay, the job, or the employer) but its relationship to improved

performance has been inconsistent and sometimes disappointing (sometimes a positive but

sometimes no effect on performance). Also, there is little evidence about the effects of skill-based

pay on productivity.

Rochat (1998) studied gainsharing in 37 organizations and concluded that such plans

were markedly successful. She identified several correlates associated with gainsharing success.

For example, a non-union environment, more frequent payout periods, less complex and better

communicated plans, and less use of a consultant in plan design were associated with more

effective plans. The success of gainsharing (e.g., lower production costs) has also been shown to

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be, in part, related to the cumulative number of implemented employee suggestions (Arthur &

Huntley, 2005).

Early research found that firms with a higher percentage of managers eligible for stock

options had higher returns on assets than firms with a lower percentage of managers eligible

(Gerhart & Milkovich, 1990). More recently, there has been debate about the consequences of

stock options, in part driven by examples where executives have manipulated stock prices for

personal gain (Rynes et al. 2005) and in part driven by recent research that has shown stock

options sometimes have negative consequences. For example, Sanders and Hambrick (2007)

found that the more a CEO is paid in stock options, the more extreme the subsequent

performance of the CEO‟s firm and the more likely that the extreme performance will be a big

loss rather than a big gain. O'Connor, Priem, Coombs, and Gilley (2006) found that increasing

CEO stock options led to less fraudulent financial reporting when CEO duality (i.e., the CEO

also serves as the chair of the firm‟s board of directors) and board stock options were either

simultaneously present or simultaneously absent, but led to more fraudulent financial reporting

when either CEO duality or board stock options was present while the other was absent.

Prior to June 2005, there was no requirement that stock options granted to employees had

to be recognized as an expense on the firm‟s income statement, although their cost was disclosed

in footnotes to financial statements. Stock options are likely to be less attractive to many firms

since 2005 when the Financial Accounting Standards Board began to require that companies

treat employee stock option compensation as an expense on corporate income statements

(thereby making the cost of such options more transparent).

One question of practical importance is how strong the link should be between

performance and pay. Although stronger links should enhance employee motivation and

55

performance, they might also have unintended side effects such as employees focusing only on

criteria that are rewarded (e.g., attending only to quantity when quantity, but not quality, is

rewarded) or manipulating (or gaming) the system (e.g., by artificially inflating results measures)

to receive short-term plan payouts at the expense of the organization‟s long-term well-being

(Rynes et al. 2005).

Despite the potential benefits of pay for performance, Beer and Cannon (2004) have

described case studies where managers thought (a) the costs of pay-for-performance programs

exceeded their benefits, and (b) alternatives such as effective leadership, clear goals, coaching,

and training were a better investment.

In sum, research indicates that pay for performance can have very positive effects on

performance although problems can occur when such programs are poorly implemented (see

reviews by Heneman & Gresham, 1998; Rynes et al., 2005). However, much of the research

about pay for performance is based on studies where an objective performance measure was

available. This raises the question of whether pay for performance is useful in the many settings

where no objective measure of performance is available and hence performance is assessed via

ratings (which suffer from poor inter-rater reliability).

In addition to their effects on performance, Rynes et al. (1995) note that pay for

performance plans can potentially create sorting effects that lead different types of people to

apply to and stay with the organization. For example, individuals with high ability (Trank,

Rynes, & Bretz, 2002; Trevor, Gerhart, & Boudreau, 1997), self-efficacy (Cable & Judge, 1994)

and need for achievement (Bretz, Ash, & Dreher, 1989) appear to be more attracted to

organizations where pay is closely linked to individual performance.

Behavioral Management Programs

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A recent meta-analysis (Stajkovic & Luthans, 2003) found that behavioral management

programs (sometimes referred to as organizational behavior modification), which are based on

the premise that behaviors that enhance performance must be contingently reinforced, led to a

16% increase in performance (d = .47) and that the greatest effect was obtained when three

reinforcers - money, feedback, and social recognition - were used in combination (45% increase

in performance) rather than separately. Earlier, Stajkovic and Luthans (1997) found that the

effect of behavioral management programs was much greater in manufacturing than in service

organizations.

Do External Rewards Diminish Intrinsic Motivation?

Deci and Ryan‟s cognitive evaluation theory (CET) states that psychological needs for

autonomy and competence underlie intrinsic motivation, hence the effects of a reward on

intrinsic motivation depend on how it affects the recipient‟s perceived self-determination and

perceived competence. That is, it is not the reward per se but rather the reward's meaning to the

recipient that determines its effect on intrinsic motivation. CET proposes that rewards that

enhance perceived self-determination or perceived competence will increase intrinsic motivation

whereas rewards that diminish perceived self-determination or perceived competence will

decrease intrinsic motivation (Deci, Koestner, & Ryan, 1999). A meta-analysis by Deci et al.

(1999) examined the effects of tangible rewards and verbal rewards (positive feedback) on

intrinsic motivation in experiments with children and college students (with activities ranging

from word games to construction puzzles and rewards ranging from dollar bills to

marshmallows). Verbal rewards (positive feedback) enhanced intrinsic motivation (for college

students) presumably because they affirmed the recipient‟s competence, however tangible

rewards lowered intrinsic motivation. It is noteworthy that verbal rewards enhanced intrinsic

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motivation when the feedback was perceived as informational but lowered intrinsic motivation

when the feedback was perceived as controlling (e.g., “you performed well, just as you should”).

Feedback can be delivered in an informational (rather than a controlling) style by praising good

performance without trying to use rewards to try to strengthen or control the behavior, providing

the recipient with choice about how to do the task, emphasizing the interesting or challenging

aspects of the task, and avoiding the use of an authoritarian or pressuring style (Deci et al.,

1999).

In sum, according to CET the effect of rewards on intrinsic motivation depends on the

meaning of the reward to the recipient. Also, research on CET has been conducted almost

exclusively with children and college students in laboratory settings; there is no evidence that

workplace rewards lower the intrinsic motivation of employees.

Special Topics in Performance Management

Managing Contextual Performance

Tippins and Coverdale (2009) argue that performance management programs should

incorporate expectations concerning contextual performance and evaluate such performance.

This makes sense because the outcomes of contextual performance can include unit or team

performance, customer satisfaction, productivity, revenue, and profits (Koys, 2001; Podsakoff,

Ahearne & MacKenzie; 1997; Podsakoff & MacKenzie, 1994; Podsakoff, MacKenzie, Paine, &

Bachrach, 2000; Sobel Lojeski, Reilly, & Dominick, 2007; Walz & Niehoff, 2000).

Contextual performance refers to behaviors such as helping coworkers, voluntarily

performing extra-role activities, persevering to complete assignments, defending the organization

to others, and following the organization‟s policies even when it is inconvenient to do so. There

are several distinctions between task performance and contextual performance. Task

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performance contributes directly to the mechanisms by which an organization produces goods

and services whereas contextual performance supports the organization‟s social and

psychological environment. Behaviors associated with task performance are usually prescribed

(e.g., listed in the job description) whereas behaviors related to contextual performance are

generally discretionary (Borman & Motowidlo, 1993; Motowidlo & Van Scotter, 1994). The

knowledge, skills, and abilities required for effective task performance usually vary depending

on the job, whereas contextual performance is related to attributes (such as personality and

motivation) that are common across all jobs. A very closely related concept is organizational

citizenship behavior (OCB), defined by Organ (1988) as “individual behavior that in the

aggregate aids organizational effectiveness, but is neither a requirement of the individual‟s job

nor directly rewarded by the formal system.” OCB has been viewed as including three factors:

helping behaviors, civic virtue, and sportsmanship (Podsakoff & Mackenzie, 1994). Borman,

Buck, Hanson, Motowidlo, Stark, and Drasgow (2001) have described three factors associated

with contextual performance: interpersonal support, organizational support, and

conscientiousness initiative. Finally, behaviors related to contextual performance can be viewed

as essential for effective teamwork (LePine, Hanson, Borman, and Motowidlo, 2000) and hence

formally recognized as job requirements.

Reilly and Aronson (2009) have reviewed antecedents of contextual performance, which

include personality (agreeableness and conscientiousness; Hurtz & Donovan, 2000) national

culture (low power distance, Paine & Organ, 2000; high collectivism, Lam, Hui, & Law, 1999),

organizational culture (e.g., norms and expectations regarding appropriate and inappropriate

behaviors), leadership (high-quality exchange relationships, supportive leader behavior, and

leader fairness; Uhl-Bein & Maslyn, 2003; Podsakoff, MacKenzie & Bommer, 1996; Schnake,

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Cochran, & Dumler, 1995; Pillai, Schruesheum & Williams, 1999), quality of feedback (Findley,

Giles, & Mossholder, 2000; Norris-Watts & Levy, 2004), and mentoring (Donaldson, Ensher, &

Grant-Vallone, 2000). Contextual performance is also related to job satisfaction (Organ & Ryan,

1995) perhaps because satisfied employees reciprocate by engaging in contextual performance

(e.g., helping coworkers) while dissatisfied employees withhold contextual performance. Organ

and Ryan‟s (1995) meta-analysis found a small positive relationship between contextual

performance and organizational commitment.

Contextual performance also explains unique variance in overall ratings of individual

performance beyond that explained by task performance (MacKenzie, Podsakoff, & Fetter, 1993;

Motowidlo & Van Scotter, 1994; Van Scotter & Motowidlo, 1996), perhaps because supervisors

reward employees for contextual performance by providing more favorable ratings (MacKenzie,

Podsakoff and Fetter, 1993). The effect of contextual performance on overall ratings of

performance appears to be especially strong in team-based cultures and among peers (Lievens,

Conway, & De Corte, 2008). Contextual performance also appears to influence formal and

informal rewards above and beyond task performance (Kiker & Motowidlo, 1999; Van Scotter,

Motowidlo, & Cross 2000). However, Reilly and Aronson (2009) note all employees do not

have an equal opportunity to display contextual performance (e.g., those who work in

collaborative settings have more opportunity than those who do not) thereby creating the

possibility that some employees would be unable to earn rewards associated with high levels of

contextual performance.

Dealing with Counterproductive Work Behavior

Spector and Fox (2005, pp. 151-152) defined counterproductive work behavior (CWB) as

“volitional acts that harm or intend to harm organizations and their stakeholders (e.g., clients, co-

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workers, customers, and supervisors).” Managers appear to place as much weight on

counterproductive behaviors as on task performance when evaluating employees (Rotundo &

Sackett, 2002). Five dimensions of CWB have been identified (Spector, Fox, Penney,

Bruursema, Goh, &Kessler, 2006): (1) abuse against others (e.g., incivility, workplace violence,

sexual harassment), (2) production deviance such as poor performance, (3) sabotage (damaging

or destroying the organization‟s property), (4) theft (potentially ranging from minor offenses

such as taking office supplies home to embezzlement), and (5) withdrawal (e.g., absenteeism,

lateness). Each of these dimensions of CWB has negative consequences for the organization.

For example, employees who experience incivility, workplace violence, or sexual harassment

report negative outcomes such as psychological distress, reduced self-esteem, lower job

satisfaction and organizational commitment, and increased intentions to quit (Cortina, Magley,

Williams, & Langhout, 2001; Fitzgerald, Drasgow, Hulin, Gelfand, & Magley, 1997; Glomb,

Munson, Hulin, Bergman, & Drasgow, 1999; Schneider, Swan, & Fitzgerald, 1997; Willness,

Steel, & Lee, 2007). Tepper, Henle, Lambert, Giacalone, and Duffy (2008) found that abusive

supervision affects affective commitment to the organization which in turn affects

counterproductive work behaviors and that this effect is stronger when coworkers approve of

organization deviance or engage in more counterproductive work behaviors.

Dealing effectively with CWB requires accurately diagnosing the cause of the problem.

Employees are more likely to attribute their performance problems to external causes than are

observers (Ilgen & Davis, 2000). Attributing poor performance or behavior to internal causes

(the employee‟s lack of effort or ability) is especially likely when the employee has a history of

poor performance (Mitchell & Wood, 1980). A review by Atwater and Elkins (2009) indicates

that the causes of CWB can include drug and alcohol abuse, family problems (such as divorce, ill

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parents, ill children), financial problems, the employee‟s personality (e.g., trait anger),

interpersonal conflict in the workplace, abusive supervision or toxic leadership (Goldman, 2006),

coworkers who are disruptive, uncivil, or bullies, feelings of injustice (either distributive,

procedural, or interactional), job dissatisfaction, situational constraints (inadequate resources or

training), and organizational climate (e.g., concerning ethics or sexual harassment).

Research indicates that managers typically have a preference for handling performance

problems in ways that do not require bold or and complicated confrontation (Morris, Gaveras,

Baker, & Coursey, 1990) perhaps by helping the employee correct the undesirable behavior

without making an issue out of the problem, identifying adjustments in work arrangements that

might reduce or eliminate the problem (e.g., changing an employee‟s work schedule who has

difficulty arriving on time due to problems at home), or restating performance expectations in a

group setting. Unfortunately, it is not uncommon to delay (or entirely avoid) giving feedback to

poor performers or to distort such feedback to make it appear less negative (Larson, 1986; Bond

& Anderson, 1987). Recognizing positive aspects of an employee‟s performance can sometimes

mitigate negative reactions to negative feedback (Lizzio, Wilson, Gilchrist, Gallois, 2003).

Research shows that managers typically consider a number of factors when considering

punishment. These include the employees‟ work history (Butterfield, Trevino, & Ball, 1996), the

severity of the offense, (Rosen & Jerdee, 1974; Liden, Wayne, Judge, Sparrowe, Kraimer, &

Franz, 1999), the effect on the employee‟s family (Butterfield, Trevino, & Ball, 1996) and the

extent to which the manager likes the employee (Fandt, Labig, & Urich, 1990). The manager‟s

attributions concerning the cause of the performance problem also plays a role such that more

serious sanctions are associated with internal (rather than external) causes (Liden et al., 1999).

Of course, punishment can have negative effects on recipients (Atwater & Elkins, 2009) such as

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embarrassment, anger, loss of respect for the manager, and bad feelings about the organization.

Consistent with social learning theory, punishment, when it is perceived as appropriate, can have

positive consequences on observers. (Atwater & Elkins, 2009) such as enhanced motivation,

satisfaction, and performance, and the absence of punishment when it was deserved can increase

observers‟ feelings of inequity (O‟Reilly & Puffer, 1989). A recent meta-analysis (Podsakoff,

Bommer, Podsakoff, & MacKenzie, 2006) found that the relationship between punishment and

employee performance was more positive when punishment was contingent (on negative

behavior) as opposed to noncontingent (the recipient does not understand what led to the

punishment).

Finally, there are a number of legal issues associated with employee discipline and

termination (Atwater & Elkins, 2009) such as employment at will (including statutory exceptions

such as the National Labor Relations Act, the Fair Labor Standards Act, Title VII of the Civil

Rights Act, the Age Discrimination in Employment Act, the Americans with Disabilities Act,

and others, and common law exceptions such as implied contract, covenant of good faith and fair

dealing, and public policy), collective bargain contracts, and negligent retention.

Managing Team Performance

Kozlowski and Ilgen (2006) presented a comprehensive review of research related to

enhancing the effectiveness of work teams. Effective teams perform well (as judged by relevant

others), have satisfied members, and are viable (i.e., members are willing to remain in the team).

Kozlowski and Ilgen reviewed the (a) cognitive, (b) interpersonal, motivational, and affective,

and (c) behavioral processes that influence team effectiveness. Important team cognitive

processes include team climate, team mental models (e.g., shared knowledge structures or

information), transactive memory, (i.e., members‟ understanding of the unique knowledge held

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by individual team members or „who knows what‟), and team learning (i.e., team members

acquiring knowledge and skills through experience and interaction). Interpersonal, motivational,

and affective processes include team cohesion, team efficacy (i.e., a shared belief in the team‟s

ability to attain a given level of performance on a specific task) and potency (i.e., a shared belief

in the team‟s ability to be effective across multiple tasks and contexts), team affect (i.e., the

mean and dispersion of affect across team members), and team conflict. Behavioral processes

include coordination of effort and actions (while reducing social loafing), team member

competencies (see Cannon-Bowers & Salas, 1997; Cannon-Bowers, Tannenbaum, Salas, &

Volpe, 1995; Fleishman & Zaccaro, 1992; Stevens & Campion, 1994, 1999), and team regulation

(e.g., the ability of the team to self-regulate and adapt to shifting circumstances and demands).

Kozlowski, Watola, Jensen, Kim, and Botero (2009) have developed a prescriptive meta-

theory of team leadership that shows how the role and focus of team leaders needs to evolve as

the team progresses through several phases over time. For example, during the first phase (team

formation), the leader adopts the role of mentor and focuses on helping members identify with

the team and commit to its mission, values, and goals. During the second phase (task and role

development), the leader adopts the role of instructor and focuses on helping members develop

individual task mastery that will lead to effective team performance in later phases. During the

third phase (team development), the leader adopts the role of coach and focuses on teamwork

capability by promoting coordination and trust among team members. During the fourth phase

(team improvement), the leader adopts the role of facilitator and focuses on adaptive capability

(i.e., the ability to rapidly respond to novel and changing task demands). Within each of these

phases, there is a distinct cycle of preparation, action, and reflection.

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Salas, Weaver, Rosen, and Smith-Jentsch (2009) describe four capacities that should play

an important role in team performance management: adaptive capacity (the ability of the team to

maintain focus on its environment so that it can adjust and align its efforts to that environment

and thereby maximize its performance), leadership capacity (the ability of the team leader and

members to set direction for the team and guide the team‟s activities in that direction),

management capacity (the ability of the team to use its resources effectively and efficiently), and

technical capacity (the ability to effectively and efficiently deliver products and services to

customers). Salas et al. (2009) also describe several research-based approaches to build each of

these capacities.

Building adaptive capacity requires developing flexible and adaptive team members (who

can engage in mutual performance monitoring and back-up behavior in an atmosphere of mutual

trust) who have a large repertoire of possible task strategies (allowing them to switch to a more

effective strategy based on situational demands). Simulation-based training can allow teams to

practice different task strategies in environments that replicate the real world but without the

risks associated with failure (Salas, Priest, Wilson, & Burke, 2006). It is also important that

teams have an awareness of their external environment as well as the internal workings of the

team. Such awareness could be developed via team cue recognition training (Salas, Cannon-

Bowers, Fiore, & Stout, 2001) and perceptual contrast training (Wilson, Burke, Priest, & Salas,

2005). Training in team communication skills can also help ensure that important changes

detected by one team member are quickly and accurately communicated to the rest of the team

(Smith-Jentsch, Zeisig, Acton, & McPherson, 1998). Also, guided error training can help teams

learn when the routine response is not the correct response and how to deal with novel situations

(Lorenzet, Salas, & Tannenbaum, 2005). Adaptive capacity requires teams that can learn from

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their past performance; this requires a team learning orientation (Bunderson & Sutcliffe, 2003)

and psychological safety (Edmondson, 1999).

To build leadership capacity, Salas et al. (2009) argue that the team‟s leader or its

members need to create a shared vision (defined in measurable terms) that is aligned with the

vision of the broader organization. The team also must manage external expectations (e.g., via

feedback seeking and ambassadorship) and have malleable individual and team goals that can be

revised to reflect unforeseen changes in the team‟s external environment. Team members also

need to offer positive reinforcement to the team as a whole for its accomplishments (as well as

support when mistakes are made), however, because of the interdependent nature of work in

most teams, caution should be exercised about using individual incentives that might undermine

cooperation.

To build management capacity, Salas et al. (2009) state that it is important to develop

measures that are diagnostic of performance (to understand „why‟ outcomes occurred), to gather

performance data from multiple sources, to measure typical (rather than maximal) team

performance continuously (so that real-time feedback can be provided), and to include teamwork

(e.g., collaboration) as well as taskwork competencies in performance evaluations.

Finally, Salas et al. (2009) note that technical capacity requires that team members are

competent at their individual tasks (taskwork) and at managing the interdependencies between

their own work and that of other team members (teamwork). Teams must be able to leverage all

of the expertise and experience on the team by ensuring that all members feel comfortable

contributing, the team has accurate transactive memory (i.e., members know who knows what on

the team), and each team member‟s input is weighted by the person‟s expertise rather than the

person‟s formal status (Hollenbeck, Ilgen, Sego, Hudlund, Major, & Phillips, 1995). It is also

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important that shared mental models are developed (via cross-training or inter-positional

knowledge training; Cooke, Cannon-Bowers, Kiekel, Rivera, Stout, & Salas, 2007). It is

desirable for team leaders to facilitate after-event reviews not only of team failures but also of

team successes because debriefing successes as well as failures can lead to greater improvement

(and yield richer mental models) that debriefing only failures (Ellis & Davidi, 2005).

Technology in Performance Management

Krauss and Snyder (2009) note growing interest in using technology to support

performance management and describe a variety of ways by which technology can facilitate the

effectiveness of performance management. For example, goals can be made accessible to all

employees and employees can easily update their goals over time. Employees can enter

information about current projects into the system (along with the contact information for the

project‟s stakeholders) and, when a project is completed, the system can automatically solicit

feedback from those stakeholders (and make the feedback available to the employee, the

manager, and designated stakeholders). Technology can help the employee and manager to

create, store, and revise a performance plan in a shared electronic workspace (especially when

the employee and manager are not co-located). An on-line database of training and

development opportunities can be linked to the plan. Sample career paths (and associated

competencies) can be available in the system and used by employees to construct their own

potential career paths and share the information with mentors or coaches. Performance data

stored in the system can be used to identify and track high potential employees, determine

appropriate developmental opportunities, and help create mentoring relationships (Stone, Stone-

Romero & Lukaszewski, 2003).

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Technology can also support completing formal appraisals, for example by generating an

initial draft narrative to be included in an employee‟s feedback report and reviewing final

appraisal narratives for discriminatory language or other statements that might raise legal

concerns (Cardy & Miller, 2003). Automated performance management systems enable easier

data entry and data extraction than paper-based systems, and can provide tools that summarize

and compare performance across employees. Automated performance management systems can

be integrated with other human resource information systems (e.g., compensation and payroll).

Despite the potential advantages of technology-supported performance management, a

number of challenges exist (Krauss & Snyder, 2009) such as information overload (Eppler &

Mengis, 2004; Klausegger, Sinkovics, & Zou, 2007), time required to input data, frustration

associated with inadequate user interfaces (Lazar, Jones, & Shneiderman, 2006), and the

requirement that users have a reasonable level of technology literacy (Marler, Liang, &

Dulebohn, 2006).

One well-established research stream related to technology and performance management

concerns electronic performance monitoring (EPM). EPM can involve the surveillance,

measurement, and recording of employee activities of employees using electronic means (Bates

& Holton, 1995; Stanton, 2000). EPM often captures performance indicators such as

productivity, accuracy, speed, and errors. EPM offers the opportunity to continuously monitor

performance (even of physically distant employees) using objective measures, but it has been

questioned by some who perceive it as an invasion of privacy that can be related to increased

stress and health complaints and lower quality work relationships (Bates & Holton, 1995; Hawk,

1994). Using EPM only for job-related activities leads to greater acceptance of EPM, reduced

perceptions of invasion of privacy, and enhanced perceptions of procedural justice perceptions

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(Alge, 2001; Grant & Higgins, 1991; McNall & Roch, 2007). Employees also report more

favorable responses to EPM when they are given discretion as to when they are monitored or

what types of tasks are monitored (Aiello & Svec, 1993; Amick & Smith, 1992). Also, more

positive attitudes occur when employees are offered an opportunity to participate in the

development of, or voice their opinions about, an EPM system (Alge, 2001; Westin, 1992).

EPM can also be used to send an automatic notice to managers when there are changes in

performance status, thereby enabling managers to provide immediate coaching and feedback.

EPMs designed for employee development rather than prevention of undesirable behavior are

also viewed more positively (Amick & Smith, 1992; Chalykoff & Kochan, 1989; Wells,

Moorman, & Werner, 2007). Finally, EPM might cause a decline in performance and

satisfaction among those still learning the task or assigned difficult performance standards

(Aiello & Kolb, 1995; Stanton, 2000).

Performance Management across Cultures

Day and Greguras (2009) note that a major obstacle to effective performance

management in multinational companies is understanding and coping with the role of national

culture. Culture shapes expectations about what is appropriate behavior.

Cross-cultural implementation of a performance management system can be fraught with

challenges (Eggebeen, 2002) such as subtle differences in the interpretation of competencies

used to evaluate performance, the willingness of managers to directly communicate negative

feedback, and the willingness of employees to provide feedback to their managers (and the

receptivity of managers to such feedback).

Project GLOBE (House, Hanges, Javidan, Dorfman, & Gupta, 2004) gathered data from

over 60 countries and 17,000 managers who represented over 950 organizations. Building on

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earlier cross-cultural research (Hofstede, 2001; Schwartz, 1994; Triandis, 1994), Project GLOBE

identified eight cultural dimensions (or practices) whose implications for performance

management have been described by Day and Greguras (2009). In high individualism cultures

(Germany, Italy, Argentina), individual goals and achievement are important and employees are

likely to change companies often, whereas in low individualism cultures (i.e., high collectivism

cultures, e.g., Japan, Singapore, Sweden) group goals, harmony, and achievement are likely to be

valued and long-term employment with the same company is more common. Nisbett and

colleagues (Nisbett, Peng, Choi, & Norenzayan, 2001) note that Easterners (generally high

collectivism cultures) are more likely to take context into consideration (leading to more external

attributions for performance) whereas Westerners (generally high individualism cultures) tend to

focus primarily on the person or object (rather than its context) and hence fail to acknowledge

the role of contextual factors (leading to more internal attributions for performance; Chiang &

Birtch, 2007). Research has also shown that employees from high collectivism cultures rate

themselves more modestly than do employees from high individualism cultures (Kurman, 2002).

In high power distance cultures (e.g., Morocco, El Salvador) people accept unequal distribution

of power in organizations and hence show considerable deference to those in authority whereas

in low power distance cultures (e.g., Israel, Netherlands) power and information are more widely

shared across organization levels and hence employees would be expected to be more

comfortable with involvement in goal setting and providing upward feedback (Peretz & Fried,

2008). In high humane orientation cultures (e.g., Ireland, Philippines) fairness, generosity,

support, and the well-being of others are especially important whereas in low humane orientation

cultures (e.g., Spain, Hungary) greater emphasis is placed on self-interest, self-enjoyment, and

material possessions. When interacting with their employees, managers from high humane

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orientation cultures might be expected to display more support, concern, and tolerance for errors

(and contextual performance in general is likely to be more valued in high humane orientation

cultures). In high uncertainty avoidance cultures (e.g., Singapore, Denmark) employees tend to

prefer order and formal procedures (e.g., clear documentation as part of the performance

management process) and are likely to show less tolerance for rule violations and more

resistance to change, whereas in low uncertainty avoidance cultures (e.g., Greece, Bolivia)

employees tend to prefer more informal interactions (and perhaps less formal feedback), trust

verbal agreements made with others, and display more tolerance for rule violations and less

resistance to change. High performance orientation cultures (e.g., Switzerland, Hong Kong)

value initiative and results and reward high performance whereas low performance orientation

cultures (e.g., Greece, Venezuela) are more likely to value and reward seniority and loyalty.

High future orientation cultures (Singapore, Netherlands) tend to delay gratification, have longer

strategic horizons, and value intrinsic motivation and long-term success (and are therefore likely

to set long-term goals and emphasize employee development and succession planning), whereas

low future orientation cultures (e.g., Russia, Argentina) place a greater emphasis on immediate

rewards and extrinsic motivation (and are therefore likely to emphasize short-term goals).

Cultures with high gender egalitarianism (e.g., Denmark, Sweden) place little or no emphasis on

an employee‟s sex in determining roles (and hence will likely provide equal opportunities for

men and women in career development) whereas cultures with low gender egalitarianism (e.g.,

Kuwait, India) are more likely to place males in powerful roles. Where gender egalitarianism is

low, female managers might face resentment (especially when conveying negative feedback);

where gender egalitarianism is high, male managers who condescend to female employees are

likely to be viewed unfavorably. Finally, high assertiveness cultures (e.g., Germany, Nigeria)

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value direct and blunt communication whereas low assertiveness cultures (e.g., Japan, New

Zealand) value modesty and face saving (and hence view assertive communication as

inappropriate). Thus, negative feedback is likely to be communicated more directly and clearly

in high assertiveness cultures.

Of course, within any country, there can be wide variations in cultural practices, hence

Day and Greguras (2009) emphasize that there is a risk in taking the generalizations associated

with these cultural dimensions too far. Moreover, the strength of the organization‟s culture

relative to national culture is an important consideration. In a strong organizational culture with

broad acceptance concerning its core values, norms, and desired behaviors, organizational

culture can trump national culture (Day & Greguras, 2009).

Perceptions of Fairness in Performance Management

Several dimensions of fairness (justice) perceptions have been identified. Procedural

justice (Leventhal, 1980) refers to whether procedures are viewed as ethical, applied

consistently, free from error and bias, and include opportunities for employees to appeal, grieve

and voice their opinions. Distributive justice refers to whether outcomes are perceived as being

fair. For example, employees will form expectations (e.g., by comparing themselves with

coworkers) regarding the performance evaluation and associated rewards they will receive. If the

actual evaluation or reward fails to meet those expectations, the outcome will be perceived as

unfair. Interactional justice is often viewed as having two components: informational and

interpersonal (Bies & Moag, 1986; Colquitt, 2001). Informational justice refers to whether

decision makers are perceived as truthful and providing an adequate explanation for an outcome,

while interpersonal justice refers to whether employees believe they have been treated with

respect and dignity. Procedural justice and interactional justice are especially important when

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performance evaluations are negative (Brockner & Wiesenfeld, 1996; Folger & Cropenzano,

1998).

Gilliland and Langdon (1998) also note that perceptions of appraisal fairness are related

to trust in supervisor, organizational commitment, and intentions to stay with the organization.

Also, some research has found small relationships between fair procedures (e.g., opportunity to

participate in the appraisal process) and changes in performance (Nathan, Mohrman, &

Milliman, 1991).

Gilliland and Langdon (1998) offered recommendations to enhance the perceived fairness

performance appraisals. These include (1) having employees provide input into the appraisal

process (e.g., via discussion with the manager prior to the appraisal being completed or by

completing self-evaluations), (2) ensuring consistent standards are applied when evaluating

different employees, (3) minimizing supervisor biases during the appraisal process (e.g., by

having ratings reviewed by the rater‟s peers or by higher-level management, (4) ensuring that

raters are familiar with the employee‟s work (e.g., by keeping a log concerning the employee‟s

work or soliciting input from coworkers), (5) ensuring that appraisal ratings and feedback are

job-related, (6) communicating performance expectations prior to the appraisal process, (7)

avoiding surprises (especially unexpected negative evaluations) by providing ongoing feedback

throughout the evaluation period, (8) ensuring that appraisal feedback is provided in an

atmosphere of respect and courtesy characterized by a two-way conversation that adopts a

cooperative, problem-solving style rather than a tell-and-sell approach; Wexley, Singh, & Yukl,

1973), (9) allowing employees to challenge or appeal their evaluation, and (10) basing

administrative decisions (decisions about compensation, promotions, etc.) on ratings.

The level of employee participation in appraisal review meetings appears to be influenced

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more by which manager conducts the review than the circumstances of the specific review

(Greller, 1998). Meta-analysis results (Cawley, Keeping, & Levy, 1998) show there is a strong

relationship between employee participation in the performance appraisal process and employee

reactions (e.g., satisfaction, acceptance, motivation) and, albeit counterintuitive, that value-

expressive participation (i.e., for the sake of having one‟s voice heard) generally had a stronger

relationship with employee reactions than did instrumental participation (i.e., to influence the

end result).

Directions for Research

Research Concerning Specific Elements of Performance Management

Taken individually, there is a well-developed research literature concerning several key

elements of performance management, especially goal setting, feedback, performance evaluation,

and some aspects of pay-for-performance. However, two key elements of performance

management deserve attention in future research: coaching and merit pay.

Coaching. One promising trend that is likely to encourage additional research can be seen

in recent efforts to develop and validate scales to assess coaching behaviors and skills (Arnold,

Arad, Rhoades, & Drasgow, 2000; Grant & Cavanagh, 2007; McLean, Yang, Kuo, Tolbert, &

Larkin, 2005; Peterson & Little, 2005). Of course, it will be important to establish that coaching

is conceptually and empirically distinct from aspects of leadership that have already been

described in well-established leadership models. For example, to what extent does coaching

overlap with directive leadership behaviors as described in path-goal theory (House, 1971)?

Coaching also appears to be an element of (or perhaps identical to) the individualized

consideration component of transformational leadership (Bass, Avolio, Jung, & Berson, 2003).

For example, Bass (1997) describes individualized consideration as including behaviors such as

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listening attentively; furthering the development of others, advising, teaching, and coaching.

And the individualized consideration scale of the Multifactor Leadership Questionnaire includes

items such as “helps others develop their strengths” (Leslie & Fleenor, 1998) and “spends time

teaching and coaching” (Mind Garden, 2008). Research that compares coaching scales to other

well-established measures of leadership can help establish the nomological net of the coaching

construct. Ultimately, it will be important for researchers to determine whether coaching can

explain variance in important outcomes beyond that explained by other models of leadership.

Bennett (2006) identified six themes for future coaching research: the coach (e.g.,

characteristics and competencies of effective coaches), the client (e.g., characteristics of clients

who benefit from coaching), the coach/client relationship (e.g., criteria for matching coaches and

clients), the process of coaching (e.g., models of coaching, the effectiveness of coaching in-

person versus over the phone), the results of coaching (e.g., sustainability of results, return on

investment), and theories related to the practice and teaching of coaching (the evidence-based,

theoretical foundations to guide coaching). Research is also needed to examine the extent to

which coaching practices need to be shaped by organizational context (e.g., organizational

cultures, small and medium vs. large enterprises), national culture (e.g., Noer, Leupold, & Valle,

2007; Peterson, 2007), and recipient characteristics (personality, experience, ability,

organizational level).

With regard to executive coaching, there is a great need for research about whether and

when executive coaching results in behavior change. As Feldman and Lankau (2005) note,

research also needs to examine whether executive coaching has a tangible effect on

organizational outcomes (rather than merely the behavior of the coaching recipient). They also

note the importance of determining whether executive coaching can, under some conditions,

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result in negative outcomes. Research needs to move beyond self-reports of the people being

coached (who generally report high levels of satisfaction with executive coaching) and beyond

short-term executive coaching interventions (e.g., with only three or four meetings) such as those

examined by Smither et al. (2003). We need studies that examine the relative effectiveness of

executive coaching compared to other developmental interventions (e.g., formal training,

multisource feedback, etc.) as well as how executive coaching might interact with (complement

or detract from) such interventions (Feldman & Lankau, 2005). It will also be important for

future research to examine factors that mediate and moderate the impact of coaching. Asking “Is

executive coaching effective?” is probably too broad a question. Because coaches use a variety

of approaches and pursue a range of goals, it will be more productive for research to examine

which coaching approaches are most effective and whether certain configurations of coaching

approaches, goals, and clients yield different outcomes than others (e.g., is approach X effective

when applied to certain goals and types of clients but not to other goals and clients?). That is, it

is possible (perhaps likely) that executive coaching will be effective in some situations but not

others. It will also be helpful to learn whether coaching provided by other organizational

members (e.g., human resource managers, organization development specialists or the

employee‟s supervisor) might be equally, more, or less effective as coaching provided by

external executive coaches. One challenge is that there are no universally accepted criteria for

what constitutes a successful outcome in executive coaching in part due to the range of activities

undertaken by coaches (MacKie, 2007). Finally, another area for future research is identifying

competencies (knowledge, skills, abilities, personality, education, work experience, and so on)

that distinguish effective coaches from less effective coaches. Note that this approach differs

from merely asking coaches what competencies are important. Instead, it first requires

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identifying more effective and less effective coaches and then assessing the competencies that

distinguish the two groups. Similarly, qualitative research is needed to determine what more (vs.

less) successful coaches actually do. Such research would require in-depth interviews with

coaches, the managers they work with, and perhaps their organizational sponsors.

Merit pay. Given the widespread use of merit pay, the absence of well-designed research

concerning its consequences reflects a major gap in our understanding of performance

management systems. There is a desperate need for research on the impact of merit pay plans on

subsequent performance (at both the individual and unit level). Rynes et al. (2005) note that such

research would ideally occur in multiple units of the same organization and, in addition to

measures of employee performance and satisfaction, would incorporate the indirect effects of

merit pay plans on promotions and the quality of employees attracted and retained. Research is

also needed to understand the causal processes (e.g., employee-level or team-level attitudes and

behaviors) that mediate the relationship between various pay for performance plans and employee,

team, and organizational performance.

Other aspects of performance management. Aguinis and Pierce (2008) have offered

directions for research about other aspects of performance management. One area concerns the

effects of the supervisor‟s power and influence. For example, will employees more readily accept

and act on feedback provided by a supervisor who is perceived as powerful (i.e., who has the ability

to influence financial rewards and other outcomes) than a supervisor who is perceived as less

powerful? Another area concerns the effects of group dynamics and close interpersonal

relationships. For example, how can performance management practices best cope with situations

where the parties involved have a close interpersonal relationship and thus a potential conflict of

interest? Another area of interest concerns communication. For example, what organizational-level

77

communication practices (e.g., descriptions of the system‟s goals and the processes involved in

implementing the system) are likely to lead to more effective systems?

Another area worthy of research attention is adaptive performance (i.e., adapting to

complex, novel, turbulent, or unpredictable work environments). For example, Kozlowski,

Gully, Brown, Salas, Smith, and Nason (2001) found that self-efficacy and knowledge structure

coherence predicted adaptive performance (i.e., generalization to a more difficult and complex

version of a task) after controlling for prior training performance and declarative knowledge.

Other research (Edmondson, Bohmer, & Pisano, 2001) has found that teams that adapt

successfully to innovative technology go through a qualitatively different learning process than

teams that do not adapt successfully. This process involves enrollment to motivate the team,

preparatory practice sessions and early trials to create psychological safety and encourage new

behaviors, and promoting shared meaning and process improvement through reflective practices.

Still, we know relatively little about how to manage adaptive performance. Research is needed

to better understand how to set goals in such environments and how to coach individuals and

teams to perform effectively as they adapt to such changes.

Performance management research will also need to consider multiple levels of analysis

(den Hartog, Boselie, & Paauwe, 2004; DeNisi, 2000). For example, performance at each level

(individual, team, organizational) affects and is affected by performance at other levels (DeNisi,

2000).

Research Concerning Performance Management Systems as a Whole

Performance management is not merely a collection of individual practices (goal setting,

feedback, coaching, and so on). Instead, these practices are presumed to be mutually

interdependent and reinforcing. That is, the impact of a well-designed and implemented

performance management system should be greater than the sum of its parts. Although

78

Schiemann (2009) notes that many organizations do not formally evaluate the impact of their

performance management systems (including how effectively the system was implemented),

approaches to do so have been described by several authors (Harper & Vilkinas, 2005; Silverman

& Muller, 2009; Spangenberg & Theron, 1997). Indeed, perhaps the most important agenda for

future research is examining the impact of performance management systems (as a whole) rather

than merely studying one or two of their elements in isolation. It appears that more acceptable

performance management system can increase trust for top management (Mayer & Davis, 1999)

yet we know almost nothing about the impact of performance management systems (as a whole)

on organizational performance.

High performance work practices (HPWPs, e.g., use of selection tests, incentive

compensation, training, performance appraisal, promotion from within) purportedly enhance

organizational performance by increasing the level of employees‟ knowledge and skills and by

empowering and motivating employees to use their knowledge and skills to benefit the

organization. A number of studies have shown that HPWPs are linked to organization-level

productivity and performance (Collins & Smith, 2006; Guest, Michie, Conway, & Sheehan,

2003; Guthrie, 2001; Huselid, 1995; Huselid, Jackson, & Schuler, 1997; Ichniowski, Shaw, &

Prennushi, 1997; Wright, Gardner, Moynihan, & Allen, 2005; Youndt & Snell, 2004; Youndt,

Snell, Dean, & Lepak, 1996; Zatzick & Iverson, 2006) although not all studies find such a

relationship (Capelli & Neumark, 2001). A meta-analysis by Combs, Yongmei, Hall, and

Ketchen (2006) found that HPWPs are related to organizational performance (r = .20) and that

the relationship is stronger for systems of HPWPs than for individual HPWPs. Unfortunately,

the design of many of these studies makes the direction of causality difficult to establish. In a

recent study designed to help establish causal direction, Birdi, Clegg, Patterson, Robinson,

79

Stride, Wall, and Wood (2008) studied the effects of operational management and human

resource practices on organizational productivity in 308 companies over 22 years. They found

positive effects from empowerment and extensive training (that were enhanced by the adoption

of teamwork), but found no direct effect of operational management practices (integrated

manufacturing and lean production) on organizational productivity. There was also a time lag

before the effects of a management practice translated into changes in organizational

productivity. For empowerment, effects were observed 1 to 4 years after its introduction

whereas for teamwork effects were observed 6 to 9 years after implementation. Although some

of these studies examined the impact of performance appraisal (e.g., behavior-based vs. results-

based), none examined the impact of performance management systems as a whole.

Future research needs to examine the impact of performance management systems using

the framework of strategic human resource management (den Hartog, Boselie, & Paauwe, 2004).

The resource-based view of the firm suggests that human resource practices can help create a

sustained competitive advantage to the extent that they help develop knowledge that becomes

embedded in the firm‟s culture and that is specific to the company. Such knowledge, which is

developed within the company rather than being imported from outside the company, is context-

specific, and hence not easily imitated by other firms (Barney, Wright, Ketchen, 2001; Wright,

Dunford, & Snell, 2001). To the extent that performance management systems link the

knowledge, skills, and competencies that are enhanced via employee development and coaching

to organization-specific goals, they hold the potential to enhance the firm‟s competitive

advantage (Lado & Wilson, 1994).

Research also needs to consider universalistic, contingency, and configuration predictions

concerning the impact of performance management practices (Delery & Doty, 1996). The

80

universalistic perspective argues that there are some best practices in human resource

management that are always better than others and that all organizations should adopt these best

practices. The contingency perspective argues that organizations adopting a particular strategy

require human resource practices that differ from those required by organizations with different

strategies. The configurational perspective focuses on bundles or ideal typologies of human

resource practices that are equally effective to the extent that there is both horizontal (i.e.,

internally consistent configurations of human resource practices) and vertical (congruence of

human resource practices with firm strategy) fit. Much of the literature related to performance

management has implicitly assumed a universalistic approach. For example, it is generally

assumed that (a) specific and difficult individual and team goals should be aligned with

organizational goals, (b) accompanied by feedback and support for employee development, and

(c) individual and team performance should be linked to rewards. But Schiemann (2009)

interviewed several leading firms about their performance management systems and concluded

that they “appear to uniquely tailor the performance management system to their strategy, culture

and management style.” For example, to the extent that organizations emphasize internal

staffing and have low employee turnover, performance management systems (with their

emphasis on feedback and employee development) are likely to play a more important role in

shaping organizational success than in organizations that rely on external staffing (where top

talent is carefully selected from the external marketplace) and perhaps have higher rates of

employee turnover. Also, the core elements of performance management (as described above)

might play a greater role in the success of firms with a defender strategy (Miles & Snow, 1978),

whereas the ability to manage adaptive performance might play a greater role in the success of

firms with a prospector strategy (with its constant search for new products and markets). Birdi et

81

al.‟s (2008) finding that the impact of extensive training varied across companies (from

substantial positive effects to weak negative effects) and Youndt et al.‟s (1996) finding that

human resource systems have a greater impact when they are aligned with manufacturing

strategy also point to the potential value of adopting a contingency framework in theorizing

about the impact of performance management systems.

It will be especially important for future research to examine not only the presence of

performance management elements and systems but also the quality of their implementation.

Moreover, the quality with which performance management systems are implemented is likely to

explain unique variance in the impact of performance management on organizational

performance.

Performance Management in the Future

Tippins and Coverdale (2009) have described workplace trends and their implications for

performance management in the future. Each of these trends points to a direction for future

research. For example, the increase in geographically dispersed teams (sometimes in different

countries and time zones) raises questions such as how to address the fact that the opportunity to

directly observe performance is no longer feasible (which is likely to pose a greater problem in

service work than production work) and how to address changes in how and when managers

interact with employees. The increasing use of outsourcing can further exacerbate such

challenges in that „team members‟ who are vital to organizational success can literally work for

another company. Although technology (videoconferencing, instant messaging, email) offers

some potential solutions to communication in geographically dispersed teams, we need to know

more about the consequences of using these technologies in place of face-to-face interactions

(e.g., how does the absence of nonverbal cues affect the effectiveness of feedback delivered

82

electronically?). Changes in worker characteristics, including predicted declines in the number of

qualified workers and changing employee expectations, also have potential implications for

performance management. How should performance management processes be designed to deal

with unskilled or under-educated workers who often lack basic literacy and numeracy skills?

How can performance management processes be modified to deal effectively with employees

who are predicted to increasingly expect opportunities for personal growth and development,

rapid career progression (which will be especially difficult as organizations tend to become

flatter), and work-family balance (and how can rewards be tailored to match the values of such

employees)?

Finally, performance management research might be shaped by emerging theory and

research from other areas of psychology such as cognitive, social, and neuroscience. For

example, Smith, Jostmann, Galinsky, and van Dijk (2008) recently found that powerlessness

impairs executive-function tasks such as updating, inhibiting, and planning, and that this

impairment is driven by goal neglect, thereby suggesting that empowering employees might

reduce costly organizational errors. Worthy, Maddox, and Markman (2007) recently showed

that regulatory fit, which increases exploration of alternative response strategies even when

exploration is suboptimal, can enhance performance on some tasks but harm performance on

other tasks. Finally, examining event-related potentials (ERPs), Mangels, Butterfield, Lamb,

Good, and Dweck (2006) found that implicit beliefs (i.e., entity vs. incremental theorists) can

influence learning success through top-down biasing of attention and conceptual processing

toward goal-congruent information. In sum, research from other areas of psychology can help

industrial and organizational psychologists ensure that their hypotheses are well-grounded in the

basic building blocks of human learning and behavior.

83

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